Dashboard-camera-based Safe Driving Support System

The 8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science Engineering (BCD 2023)


Creation and Testing of Synthetic Datasets for Training Road Scenes Algorithms

32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)


Recognizing football game events: Handball based on Computer Vision


Image-based Pretreatment Study of Rice Blast Disease

3rd International Conference on Intelligent Systems, Cognitive Science and Knowledge Engineering

Rice blight has a great impact on rice yield and can lead to yield reduction of up to 70% in severe cases. Traditional detection methods require professional technicians to operate and are costly and inefficient, and cannot detect rice diseases in real-time. In this paper, we applied image detection technology to study rice blast disease based on the Matlab platform. Firstly, a basic rice blast database is built, and then a discussion is made on how to effectively improve the recognition success rate of rice blast images by two aspects: image pre-processing and feature extraction. The main research contents are as follows. (1) After studying the existing plant disease database, a basic rice blast database was constructed by field photography and other means. (2) Preprocessing of the collected rice blight images. Using the algorithm of rgb2gray function in Matlab, the images were grayed out; based on this, median filtering was used for noise reduction; then histogram equalization technique was used for image enhancement to increase the contrast and make the images clear; finally, various segmentation algorithms were used for image segmentation. (3) For the pre-processed rice blight images, feature extraction was performed in terms of the color of the disease to pave the way for feature selection.


Pedestrian detection algorithm based on improved YOLOv3

The ability to accurately detect pedestrians in the area of interest in real time is crucial in the field of autonomous driving. An improved YOLOv3 model is proposed for pedestrian detection. Firstly, a lightweight model that incorporates a residual network module approach and a CBAM attention mechanism is added to the structure to enhance the feature representation capability of the network. Experimental results show that the improved YOLOv3 target detection model raises the detection accuracy by 4% compared to the original algorithm, and the accuracy precision is improved to a large extent, which verifies the feasibility and effectiveness of the improved YOLOv3 model for pedestrian detection.


Indoors Fitness Training Monitoring based on OpenPose

With the continuation of the COVID-19 pandemic, people's daily life has changed. The changing life habits are reflected in the increasing number of hours working at home. Mostly affected is physical fitness, because of limitations or fear of the gym/outdoors or effective exercise indoors. However, with the arrival of the post-pandemic era, although working at home has improved, the fitness problem still haunts people. Some people have become accustomed to home fitness and are no longer limited to the traditional gym or gymnasium. However, proper and safe exercising is still a challenge due to the lack of live coaching. With the advent of artificial intelligence and the improvement of virtual reality (VR) and augmented reality (AR) capabilities, the options for live off-site coaching have become feasible. This study is based on OpenPose technology in artificial intelligence to monitor the standard of people's movements in-home fitness. The study results are encouraging.


Vision-based primary localization method for SLAM mobile robots

The AMCL (Adaptive Monte Carlo Localization) algorithm with visual provision of initial values is proposed to address the slow localization speed caused by conventional laser SLAM (Simultaneous Localization and Mapping) without initial poses and the global localization failure after a robot abduction event. In the initial map building phase, the ORB (Oriented FAST and Rotated BRIEF) feature values are extracted from the camera and the wall corners are identified, and then the pose information is stored in the database and a feature dictionary is constructed. After restarting, the dictionary is called to perform loopback detection by receiving the images captured by the current camera, and a successful detection results in a rough initial pose. If the detection fails, the initial pose is roughly calculated by identifying the wall corners. Finally, the particle filtering algorithm scatters particles in a small area near the obtained pose and converges to obtain a relatively accurate pose.


Application of On-Road Surveillance Cameras for Traffic Light Optimization

Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS2022)


Appearance-based Drivers Gaze Mapping Using a Dash Camera


3D Shape Reconstruction of Puppet Head from CT Images by Machine Learning

Proceedings of the SICE Annual Conference 2022

The Society of Instrument and Control Engineers


3D Shape Reconstruction of Japanese Traditional Puppet Head from CT images

The 28th International Workshop on Frontiers of Computer Vision (IW-FCV2022)


Inner and outer 3D shape reconstruction of puppet head from CT images

SPIE The International Society for Optical Engineering


An intelligent traffic control systems using on-road cameras


Continual learning : Linear layer classier concatenation using image processing transform functions


A comparative study of batch ensemble for multi-object tracking approximations in embedded vision


Social distance measurement for indoor environments


Automatic recognition of parasitic bee species using wing vein shape

本論文では，翅脈形状による寄生蜂の種の自動認識手法を提案した．この手法は，寄生蜂から得られる翅画像から，翅脈の形状を抽出し，結節点の位置や結節点同士間の長さを特徴量に，その寄生蜂の種を自動認識することができるものである．本手法の有効性を検証するために行った実験により，寄生蜂を正しく認識することを確認した．


Piano performance support system with a head-mounted display

本論文では，VRを用いたピアノ演奏の練習支援手法を提案する．本手法では，演奏者にHMD(ヘッドマウントディスプレイ)を装着してもらい，その画面上に，押すべき鍵盤や指の使い方などを表示して，演奏を導くものである．本手法の有効性を検証するため実験の結果，初心者の演奏スキルを向上させる可能性が確認できた．


Identification of insect infiltration time by tissue slice

本論文では，食品等に混入する昆虫の凍結切片を用いることで，その混入時期を特定する手法を提案した．この手法は，顕微鏡により得られる凍結切片画像から，複数の特徴量を利用することにより，対象が加熱されているか，加熱されていないかを認識することができる．本手法の有効性を検証するための実験によって，混入時期を正確に特定することを確認できた．


3D Shape Reconstruction of Puppet Head from CT images

Proceedings of the SICE Annual Conference 2020

The Society of Instrument and Control Engineers

In this paper, we discuss a method to measure 3D shape of puppet head for a digital archiving. In order to reconstruct an inner shape of head, we use CT images. Firstly, we divide four regions (wood, hair, paint and air) by thresholds which obtained by manual directed regions. After that, we divide these regions by a graph cut method. We apply this method to a puppet head and we confirm effectiveness of our proposed method.


Facial emotion recognition using deep learning

Proceedings of IEEJ International Workshop on Sensing, Actuation, Motion Control, and Optimization2020

The Institute of Electrical Engineers of Japan


Facial emotion recognition using deep learning ls

Proceeding of the 6th IEEJ international workshop on Sensing, Actuation, Motion Control, and Optimization

Emotion recognition has played an important role in the research field of Human Computer Interactions. Therefore, there is need for wellimplemented automatic emotion recognition systems. Nowadays, Neural Networks are one of the best methods to improve emotionrecognition in this field. There are many emotions in wild data available these days. But, many of them are labeled with noise. In this work,firstly, we trained and compared state of the art models such as Resnet, Seresnet and Densenet in FERPlus dataset. After that, we decide thepre-trained model such as LRCN model for emotion recognition in video.


Risky Pedestrian Detection System using In-vehicle Camera

本稿では車載カメラを用いた危険な歩行者の検出システムを提案する．本手法では，自動車に設置された前方カメラから得られる映像に対して，深層学習を用いることで，歩行者の存在を検出した上で，その人物が走行車に対して危険であるかどうかを判断した上で，ドライバーに警告を与えることが可能である．本手法の有効性を確認するために行なった実験で，高い精度で危険な歩行者のみを検出できることが示唆された．


Tracking Owner of Detected Abandoned Luggage at Public Areas

本論文では，画像処理を用いて放置された手荷物を検出した上で，所有者の追跡する手法を提案する．この手法では公共の場所に設置された監視カメラから得られる映像から学習機能を用いて放置された手荷物を検出し，さらにその所有者を追跡することで，防犯上の問題である公共の場での放置物に対する脅威を取り除くことができる．本手法の有効性を検証する実験で，高い精度で追跡可能であることが示唆された．


Mitigating Constraints in Load Balancing and Scheduling in Embedded Systems with Ensemble Models

本稿では，アンサンブルモデルを用いた負荷分散における制約緩和と組込みシステムにおけるスケジューリング法について提案した．本手法は，複数の予測モデルを組み合わせて最終的な予測結果を出すアンサンブルモデルを用いて，負荷分散における制約の緩和と組込みシステムにおけるスケジューリングを最適化できる．本手法の有効性を確認するためのARMアーキテクチャを用いた実験により，高い性能が実現できることを示した．


Detection of Various Vehicles Using YOLO Object Detector

Proceedings of the 26th International Workshop on Frontiers of Computer Vision (IW-FCV 2020)

本論文では，YOLO(You Look Only Onse)アルゴリズムを用いて多種多様な自動車を検出する手法を提案する．この手法では，従来あるような検出窓を走査させることなく，自動車が映っている画像にCNN(Convolutional Neural Network)を適用することで，色や形，大きさの異なる多種多様な自動車を検出することが可能である．さらに実際の多種多様な自動車が映っている前方車載カメラ映像に対して本手法を適用して有効性を検証した実験について示した．


A Calibration Method of 3D Shape Measurement System Using 3D Scanner, Turn-Table and Arm-Robot

Proceedings of the SICE Annual Conference 2019

The Society of Instrument and Control Engineers

本稿では，デジタルアーカイブのための対象物全体の3次元形状計測システムについて提案する．本システムは，3Dスキャナ，アームロボット，ターンテーブルで構成されている．本手法では，システムで使用する機器の変位を計測してシステムのキャリブレーションを行なうことで，3次元形状を正確に計測することができる．本手法の有効性を検証する実験により，精度良く対象物全体の3次元形状計測が行なえることを示した．


Drowsiness Detection by Facial Features and Hand Gestures Using Deep learning

The International Council on Electrical Engineering Conference 2019(ICEE2019)

Drowsiness detection is one of the interesting research for computer vision regarding drivers fatigue. Previous studies of drowsiness detection has mainly focused on tracking of the eyes and mouth conditions like eyes blinking, yawing, and so on. The detection of hand gesture is also commonly used as the sign of drowsiness such as the hand cover on mouth and with the closure of the eyes by this hand gesture sign. The applications of this research can expand from only the observation of drowsiness for drivers to observing the status of drowsiness at other environments, for example, call center agents, control room observers, and air traffic controllers. Our proposed system integrates traditional machine learning and deep learning algorithms to increase the performance of accurate detection using four stages as the following. The first stage is the detection of eyes and mouth in the scene. The second stage is skin color detection to extract the face and hands area. The third stage is classification using deep learning to recognize the status of person. Final fourth stage is to detect the signs of drowsiness automatically. For the eyes and mouth detection, our system used a feature detection based on the Haar cascade classifiers. YCbCr color space is used for the skin-color detection if the mouth detection is failed. Three transfer learning convolutional neural network (CNN) models in order to classify the status of eyes, mouth and hand gestures. The images for evaluation were processed by MATLAB, we applied GoogLeNet learned by three datasets consists of eyes opened and closed, mouth opened and closed, and hand over mouth images. Finally, the drowsiness is successfully recognized in the following cases: (1) The eyes are closed more than normal blinking rate and less than the full closure due to sleep and open the mouth. (2) The eyes are closed and the hand covered on the mouth. The system achieved the classification ratio of drowsiness signs average 96.6 %.


Classifictaion of Hand Over Face Gestures using Deep Learning

The Fourteenth International Conference on Quality Control by Artificial Vision 2019(QCAV2019)

SPIE The International Society for Optical Engineering

FFacial expressions and hand gestures are recognized as a part of human emotions especially in a feeling of fatigue signs. In computer vision research, a positioning of hand over face is one of the challenging problem caused by difficulty of the difference of skin color for hands and face. In this paper, we present a method for classifying six positions of the hand over face which is able to identify the signs of feeling fatigue for the visual display terminal (VDT) workers. We apply a deep learning method in order to compare with the methods used the face and skin colors detection, processing the edge detection and feature extraction algorithms. In addition, GoogleNet is used for training a data set made in the simulated VDT workers environment. The data set includes 1,440 images, the participants from several countries, Egypt, Japan, Bangladesh, Mongolia and Rwanda to cover a wide range of skin tones. The data set is categorized by six groups of the positions of hand over face. These groups consist of hands on a forehead, eyes, nose, mouth, right and left face. The experiments were performed using MATLAB to implement our proposed method. The system achieved average recognition ratio 99.3 % in all hand over face gestures.


Advanced Prevention for "KAROSHI" using Artificial Intelligence

KAROSHI, death from overwork, is a well-known word, especially in Japan. There are government efforts to prevent the occurrence of KAROSHI, however, Japanese still suffer as log hours work persist. In the current research, our system can be recognized several facial features and body signs regarding of stress and fatigure caused by overwork such as a headache, neck , shoulder, and back pain. Of the recognition,we used a general webcam with PC to implemet the acritical intelligence algorithm. Our AI system has achieved the recognition of stress and fatigure signs precisely with high accuracy of 95.0%. This system contributes to restrain Japanese KAROSHI in the near future.


Multi-People Tracking in Indoor Video Surveillance System

the 5th IEEJ international workshop on Sensing, Actuation, Motion Control, and Optimization (SAMCON2019)

The Institute of Electrical Engineers of Japan

本稿では，屋内監視カメラから得られる映像から複数人物の追跡手法を提案する．屋内では人同士が密集しやすく重なりやすく，さらに各々の人の歩く速度や姿勢が大きく変わるため，個々の人の追跡が難しい．本手法では，カルマンフィルタを改良して適用することで，予測しながら複数の人を同時に追跡することを可能にした．本手法の有効性を検証する実験で，高い精度で複数人物を追跡できることを示した．


Human Interaction Recognition Based on Deep Learning

Proceedings of Annual conference on Engineering and Information Technology(ACEAIT2019)

本稿では，深層学習による人のインタラクションの認識手法を提案する．人の動きの認識は動画像処理の分野で注目されているが，近年，深層学習の導入で大きな成果をあげている．本手法では連続フレームにおいて，深層学習を用いることで隠れている時間や空間の問題を解決し，人の動きを認識する．本手法の有効性を検証するためのベンチマークのデータセットを用いた実験により，人の動きを高い精度で認識できることを示した．


Vision-Based Vehicle Recognition Classification Using Convolutional Neural Network and Support Vector Machine

本稿では，改良型のAlexNetを用いた実道路環境下における車両領域抽出と分類手法を提案する．本手法では，車両領域抽出のロバスト性の低さを，高速で軽量化したYOLOを用いて解決し，さらに深層学習とSVMを組み合わせて，SVMで特徴量を正規化することで，モデルの汎化能力を向上させている．本手法の有効性を検証するための実験により，車両検出と車種分類を従来手法よりも高い精度で実行できることを示した．


Automatic Recognition of Road Marking using CNN

Proceedings of International Research Conference on Engineering and Technology(IRSET2019)

本稿では，深層学習を用いて，路面標識を自動認識する手法を提案した．本手法では，まず自動車の前方に取り付けられた車載カメラにより連続的に撮像された映像から生成される時空間画像から精度良く道路標示領域を抽出した上で，CNNを用いて道路標示を認識し，その結果を音声ガイドと画面表示で運転者に伝えることができる．本手法の有効性を検証する実験で，精度良く路面標識を自動認識できることが示唆された．


Recognition of Fatigue Sings using Artificial Intelligence

Proceedings of the 1st Scinetific Conference Advanced and New Approaches in Physical Therapy

The shoulder, neck and lower back pains, as well as headaches caused by eyestrain, are among the most common signs of fatigue due to by sitting in front of the computer long time without taking rest or exercise. In this paper, we present a proposal for a database of images that include hand poses with the head, shoulders and neck as the signs of fatigue. The database includes images taken by eight cameras with different angles and cover a wide range of human skin color. We introduce a system to recognize the fatigue signs Based on the Artificial Intelligent (Al) algorithms. The machine learning (ML) is used for face detection and human skin-color. The deep learning(DL) is used for classification of hand poses with the head, neck and shoulders.As the results, we have achieved high accuracy of detection and classification, 92% for face detection, 99 % for skin-color detection and 85 % for classification of hand poses.


Robust Detection and Tracking of Moving Objects Using Particle Filter

Proceedings of Annual Conference on Engineering and Applied Science (ACEAT2018)

本稿では，パーティクルフィルタを用いた移動物体の検出と追跡手法を提案した．本手法では，連続して撮像される映像からHOG特徴とSVMを用いて人の領域を抽出し，パーティクルフィルタを用いて人の動きを追跡することで，人同士が重なる混雑時や照明環境の変動にロバストにすることを可能にしている．本手法の有効性を検証する実験により，環境変動にロバストに移動物体の検出と追跡ができることを示した．


Traffic volume survey Using Convolutional Neural Network

本稿では，道路監視カメラを用いた深層学習による交通流監視法を提案する．本手法は，道路上方に設置された監視カメラから得られる映像より，車両領域を検出した上で，乗用車，軽自動車，小型貨物車，普通貨物車，バス・大型車のいずれであるかを深層学習により認識し，車種別の交通量を計測することができる．本手法の有効性を検証するために行なった実験により，車種別の交通量を高い精度で計測できることを示した．


Visual Fatigue Recognition Using Facial Features and Hand Poses for VDT Workers

Proceedings of the International Conference on Electrical Engineering (ICEE2018)

画像処理を用いてVDT作業者の疲労動作の認識手法を提案した．本手法ではディスプレイに装着されたカメラから得られる映像を用いて，VDT作業者の疲労具合を手の動きや顔の特徴量によって自動認識する手法である．ここでは肌色領域の変化に着目することで，顔や手の動きに検出し，さらにあくぶ，ほおづえ，目のマッサージなどの姿勢を認識する手法を開発した．さらに本手法の有効性を検証する実験において，約90%の精度で認識することができた．


Proceedings of The 5th Annual Conference on Engineering and Information Technology(2018ACEAIT)

カメラ映像を用いて，カルマンフィルタとサポートベクターマシーンを用いて人の行動監視をする手法を提案した．本手法では画像処理を用いて人を検出し，さらにカルマンフィルタを用いて追跡することで，人の行動を監視できるものである．これにより歩いている人，ジョギングをする人，走っている人を認識することが可能である．本手法の有効性を検証するために実験をしたところ，約70%の精度で人の行動を認識することができることがわかった．


Road Sign Character Recognition On a Smart phone using Deep Learning

4th International Forum on Advanced Technologies

本論文では，スマートフォンで撮影された画像を用いて，道路標識上の文字を認識する手法を提案した．本システムでは，スマートフォンで道路標識を撮影した画像から文字列を抽出し，ディープラーニングを用いて文字認識することができる．さらに文字認識した情報を用いて，GPSで取得した現在位置とGoogleMapを用いて外国人旅行向けのナビゲーションシステムを構築した．本手法の有効性を検証したところ，約83%の精度で文字認識できることがわかった．


Body Physical Parameters Measurement using Kinect

4th International Forum on Advanced Technologie

本論文では，RGB-Dカメラを用いて，人の形状を計測するシステムを提案した．本システムは，Kinectを用いて人の3次元形状を取得した上で，被験者の身長，座高，肩幅，股下，全頭高，膝下，股上，頭身，ウエスト，腕の太さ，わたり幅，首の太さなどの人の各部位のサイズを計測することができる．本手法を用いることで服を仮想的に試着することができる．本手法の有効性を検証したところ，各部位のサイズを誤差5cm以内で計測することがわかった．


Real time backpack detection in visual surveillance based On verticals contour analysis

6th IIAE International Conference on Industrial Application Engineering 2018

本論文では，監視カメラから得られる歩行者が持ち歩くバックパックとスリングバッグを画像処理によって検出する手法を提案した．この手法では，人体の内部または近くに発生する垂直線を見つけた上で，いくつかのファジールールを使用して等高線を作成した上でバックパックとスリングバッグを検出することができる．本手法の有効性を検証するたにVIRAT ground video datasetを用いて実験をしたところ，高い精度を得られることがわかった．


Household Items Recognition using Distance Sensor Equipped Video Sunglasses

Risp International Workshop on Nonlinear Circuits, Communications and Signal Processing

The Research Institute of Signal Processing Japan

本稿では，目の不自由な人が台所等で作業するために，家庭用品を認識した上で，手にとりやすいように位置を計測する手法を提案する．この手法では，サングラス型カメラから得られる映像を処理することにより道具の種類を認識して，さらにサングラス型カメラに搭載されている距離センサにより位置を推定することが可能である．本手法の有効性を検証する実験で，目の不自由な方の作業の支援が可能であることが示唆された．


Motion-Based Detection and Tracking of Multiple Pedestrians

19th International Conference on Computer Vision and Machine Learning(ICCVML2017)

本論文では，画像処理を用いて，複数の人の検出と追跡ができる手法を提案した．本手法では，背景差分を用いて人領域を抽出した上で，GMMを用いることで映像の中から移動する人を決定し，さらにカルマンフィルタによって人の追跡することができる．本手法を用いることで進行方向別の人数を計測することが可能となる．本手法の有効性を検証するために実験を行なったところ，約87%の精度で人が検出でき，約77%の精度で人が追跡できることがわかった．


Burnout Recognition for Call Center Agents by Using Skin Color Detection with Hand Poses

19th International Conference on Science, Engineering and Technology(ICSET2017)

本論文では，ディスプレイ上の設置されたカメラ画像から顔周辺での手の動きに着目したVDT作業者の疲労度認識手法を提案した．本手法ではカメラから連続的に得られる映像を用いて，手が肩や首をもむ動作を認識することで被験者の疲労具合を認識するものである．本手法の有効性を検証するために，実際に正常な被験者と，疲労した被験者に対して実験を行なったところ，高い精度で検出で疲労具合を認識できることがわかった．


Body Physical Measurement using Kinect for Virtual Dressing Room

Proceedings of the 6th IIAI International Congress on Advanced Applied Informatics( IIAI-AAI 2017)

本論文では，3DCGを用いた疑似試着システムを提案した．この手法では，RGB-Dカメラを用いて被験者の3Dデータを取得した上で3Dモデルを作成し，さらに予め作成してある服のデータを用いて，仮想空間上で疑似試着をするものである．3Dモデルでは，身長，首の太さ，腕の太さ，ウエストなどの試着に必要なサイズを取得することで，服のフィット感を3DCGで確認できる．実際にKinectを用いた実験によって，本手法の有効性を確認した．


Character Recognition in Road Signs using a Smartphone

本論文では，スマートフォンを用いた道路標識上の文字を認識する手法を提案した．この手法では，スマートフォンで撮影された道路標識に対して，端末上でタップした文字列を認識することができる．本手法では認識にはディープラーニングを用い，さらにGoogle Map APIを適用することで，現在地から目的地までのナビゲーションをすることが可能である．本手法の有効性を検証するために行った実シーンによる実験によって，高精度に文字を認識することがわかった．


Real Time Specified Person Tracking in a Crowded Scene using the Particle Filter

Proceedings of the International Conference on Electrical Engineering (ICEE2017)

本論文では，パーティクルフィルタを用いて，混雑環境下において，人を追跡する手法を提案した．この手法では，まず取得された映像からHOG特徴とサポートベクターマシーンを用いて人の領域を検出した上で，パーティクルフィルタを適用して人を追跡するものであり，複数の人を追跡することができる．本手法の有効性を検証するために実験を行なったところ，人の検出では約90%，人の追跡では約98%の精度を得ることができた．


Drone Control using Visual Natural Markers

Proceedings of the 2017 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'17)

本論文では，ドローンの自動制御のために，ビジュアルマーカ―を用いたドローン制御手法を提案した．本手法では，ドローンに搭載されているカメラから得らる映像にマーカ検出と追跡に画像処理を適用し，ドローンの安定した自動飛行及び自動着陸等を容易にした．さらに実際にドローンを飛行させて，挙動を自動制御した実験においても，精度の良いマーカの検出と追跡，さらに安定した飛行と着陸が可能であることを確認することができた．


Safe Driving Support System using Three Onboard Camera

本論文では，3台の車載カメラを用いて，運転者に危険を知らせ，安全運転を支援するシステムを提案した．この手法では，前方カメラでは車線や歩行者，右折車や右折時の直進車，後方カメラでは車線変更の際の後方走行車等を検知した上で，運転者監視で得られる顔の向きと視線の向きと連動させることで安全運転を支援するものである．実際の車載カメラ映像を用いた実験によって，高精度に危険を検知することが可能であることがわかった．


Upper Back Pain Detection System by Monitoring VDT Workers Pose and Eyes

Proceedings of International Workshop on Frontiers of Computer Vision

本論文では，VDT作業者の疲労から生じる背中上部のこりや痛みを検出する手法を提案する．この手法では，まずディスプレイに設置されたカメラから得られる映像から肌色に着目して顔領域と手領域を検出する．そして顔領域内からは目領域を検出した上で目の開閉具合を検知，手領域の位置を計測した上で肩に手がかかっているかを検知することで，被験者の背中上部のこり具合を検出する．さらに本手法の有効性を検証した実験について示した．


Intelligent Driver Support Systems: Pedestrian Detection Using HOG Algorithm

Proceedings of the 4th IIAE International Conference on Intelligent Systems and Image Processing


Counting People Utilizing Space-Time Imagery

18th International Conference on Image and Vision Computing(ICIVC2016)

Counting people and observing their movements are useful processes for various purposes, for example security, organizational administration, and improving corporate business results. This paper introduces an automated method for counting passersby using virtual-vertical measurement lines. The process of recognizing a passerby and generating space-time images is based on a sequence of images obtained from a USB camera. Space-time imagery represents recognizable human regions (shapes), which are processed using a labeling-based segmentation. In this study, space-time image represents the time as a pixel-distance, which is used to support the algorithm to achieve accurate counting. . Human regions are detected using space colors based template matching that automatically selects the optimal match in order to obtain direction and speed. Whether the shape represents only one or two passersby can be ascertained using the relationship between the passerby speed and the human-pixel area. To verify the effectiveness of the proposed method, we performed experiments using a side view camera is placed near the entrance. A counting and direction accuracy of 97% was achieved.


3-Dimensional Space Modeling using Kinect

Proceedings of the 34th Chinese Control Conference and SICE Annual Conference2015(CCC&SICE2015)

本論文では，RGB-Dカメラから得られるデータを用いて，3次元モデルを生成する手法を提案した．これは特殊な装置を使ったり，厳密なキャリブレーションしたりすることなく取得した3次元データから，回転不変位相限定相関法と位相限定相関法を用いて高精度な3次元モデリングができる手法である．本稿では，さらにいくつかのシーンに対して，Kinectを用いて得られたRGB-Dデータから，高精度に3次元モデルを生成できることを示した．


Tire Cracks Detection using Image Processing

Proceedings of the first IEEJ international workshop on Sensing, Actuation, and Motion CONtrol(SAMCON2015)

本論文では，画像処理によって黒色のタイヤに存在する黒色のひび割れを検出する手法を提案した．本手法では，まず取得画像に対して，タイヤの円弧方向に極座標変換することによって直行座標画像に変換する．さらにウェーブレット変換を用いて高周波領域に着目して候補領域として抽出した後，輝度や連続性の特徴量によってひび割れであるかを評価する．さらに実際に撮影されたタイヤのひび割れ画像を用いて，本手法の有効性を検証した．


Elderly Monitoring System using Surveillance Cameras

Proceedings of the 2015 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing(NCSP'15)

本論文では，室内に設置された監視カメラから得られる映像を用いて，行動を解析する手法を提案している．この手法では，高齢者養護施設や高齢者独居住居に設置されたカメラ映像から，主に高齢者の行動を認識するもので，転倒，作業，視聴，運動，休憩，冷蔵庫等の開け閉め，静止，移動などの行動を認識して，もし危険があれば通知することができる．さらに実際に製作した簡易的な部屋における実験によって，本手法の有効性を検証した．


Input Interface using Air Character Recognition

本論文では，空中に書かれたAir文字を認識する手法を提案した．本手法は紙やタッチパネルに書かれた文字ではなく，空中に指で書いた文字をカメラ映像によって，その指の動きを追跡することでその文字を認識する手法である．本手法ではカタカナで書かれた文字を認識することが可能だけでなく，消去，リセット，決定などを認識する実用的な手法となっている．さらに実際に空中に書かれた文字を認識する実験で，本手法の有効性を検証した．


Road Surface Marking Recognition Using Neural Network

Proceedings of the2014 IEEE/SICE International Symposium on System Integration(SII2014)

In recent years, the number of traffic accidents has rapidly increased. There are various reasons for this, but as one of the most common one is the carelessness of the driver. Therefore, we aim to decrease the number of traffic accidents by automatically recognizing the road signs and informing the driver accordingly. In the proposed method, at first, we use the edge information and after transform it, we can extract the target road area. The road marking candidate is then extracted and recognized using a neural network.


Indoor Human Action Recognition using Multi Camera

Proceedings of the IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision Processing (CIMSIVP'14)

In this paper, we propose a method for recognition of human actions using multi cameras especially for the detection of suspicious humans. In human region detection, we use background difference and HOG features, with the learning data for HOG made by AdaBoost. We decide whether the detected human is moving or not using the distance of the detected area between frames. We also estimate the direction the human is facing using the width of detection, and finally recognize the standard action using the height measured from the direction. In addition, we recognize suspicious action using duration of detection and presence of abandoned object. Recognition accuracies for walking and stop actions are about 87% , for running action about 54%, for sitting about 96%, for desk working about 83%, and falling about 88%.


Human Action Recognition using Normalized Cone Histogram Features

Proceedings of the IEEE Symposium Series on Computational Intelligence (CIMSIVP 2014)

In this paper, we propose a normalized cone histogram features method to recognize human actions in video clips. The cone features are extracted based not on the center of gravity as is common, but on the head position of the extracted human region. Initially, the head, hands and legs positions are determined. Thereafter, the distances and orientations between the head and the hands and legs are the extracted and employed as the features. The histogram's x-axis represents the orientations and the y-axis the distances. To make the method invariant to human region sizes, the features are normalized using the L2 normalization technique. The classification method used was the perceptron neural network. We conducted experiments using the ucf-sports-actions database to verify the effective ness of our approach. We achieved an accuracy of about 75% on a selected test set.


A GA - ACO Hybrid Algorithm for the Multi - UAV Mission Planning Problem

Proceedings of the 14th International Symposium on Communication s and Information Technologies(ISCIT2014)

Multi-UAV mission planning is a combinational optimization problem, that aims at planning a set of paths for UAVs to visit targets in order to collect the maximum surveillance benefits, while satisfying some constraints. In this paper, a genetic algorithm and ant colony optimization hybrid algorithm is proposed to solve the multi-UAV mission planning. The basic idea of the proposed hybrid algorithm is replacing the bad individuals of the GA's population by new individuals constructed by ant colony algorithm. Also, an efficient recombination operator called path relinking is used for mating. A population partition strategy is adopted for improving the evolving efficiency. Experimental results suggested that the proposed hybrid algorithm can solve the test instances effectively in a reasonable time. The comparison study with several existing algorithms shows that the proposed algorithm is competitive and promising.


Vehicle Extraction from Aerial Images Captured using an UAV

Proceedings of the 2014 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing(NCSP'14)


Human Action Recognition using Multi Cameras

Suspicious person must be detected at important sensitive institutions like airports, train stations, sports arenas, etc. to maintain safety at these locations. In this paper, we propose the method for recognition of human actions using multi cameras for detection of suspicious persons. In the process for detecting human, we use background difference and HOG features, leaning data for HOG is made by AdaBoost. We judge whether the detected person is moving or not using the distance of the detection area between frames. We also estimate the direction the person is facing using width of detection, and finally recognize the standard action using attitude measured from the direction. In addition, we recognize suspicious action using duration of detection and presence of left object. Recognition accuracies for walking and stop actions are about 87% , for running action about 54%, and for sitting about 96%.


Motion analysis of an aquarium fish using a Web camera

It is very popular to been a pet with recent years. Especially Tropical Fish is very popular in Japan. However, is difficult to breed Tropical Fish. There for, we proposal a method of motion analysis of Tropical Fish by using a web camera, and early detection of the abnormalities. Background difference is performed in order to extract an Tropical Fish. When a fish overlaps and it waits, it divides using Snakes. When a fish is missed, supplementary pursuit is performed using Particle Filter. These processing perform Individual pursuit of tropical fish.


Japanese Road Signs Recognition using Neural Networks

Recently, traffic accidents are increasing because of driver's inattentiveness to the road signs. In this work, in order to assist drivers, we propose a recognition system for road signs using neural networks. We first segment road sign regions using color and shape features to get the location information. The initial sign recognition uses template matching. However, since this did not produce satisfactory results, a neural network is used to learn and recognize the signs. A variety of features are considered for training the neural network. The experimental results show that this recognition method is effective for online road sign recognition.


Hand Written Character Recognition using Star-Layered Histogram Features

Proceedings of SICE Annual Conference 2013

In this paper, we present a character recognition method using features extracted from a star layered histogram and trained using neural networks. After several image preprocessing steps, the character region is extracted. Its contour is then used to determine the center of gravity (COG). This CoG point is used as the origin to create a histogram using equally spaced lines extending from the CoG to the contour. The first point the line touches the character represents the first layer of the histogram. If the line extension has not reached the region boundary, the next hit represents the second layer of the histogram. This process is repeated until the line touches the boundary of the character's region. After normalization, these features are used to train a neural network. This method achieves an accuracy of about 93% using the MNIST database of handwritten digits.


Japanese Road Signs Recognition Using Neural Networks

Proceedings of the International conference on Instrumentation, Control, Information Technology and System Integration(SICE Annual Conference 2013)

The Society of Instrument and Control Engineers

Recently, traffic accidents are increasing because of drivers inattentiveness to the road signs. In this work, in order to assist drivers, we propose a recognition system for road signs using neural networks. We first segment road sign regions using color and shape features to get the location information. The initial sign recognition uses template matching. However, since this did not produce satisfactory results, a neural network is used to learn and recognize the signs. A variety of features are considered for training the neural network. The experimental results show that this recognition method is effective for online road sign recognition.


Automatic Detection of Suspicious Objects Using Surveillance Cameras

Suspicious objects must be detected at important sensitive institutions like airports, train stations, sports arenas, etc. In this paper, we propose a method for automatic detection of suspicious object using a surveillance camera. Person and object areas are extracted using the current frame, previous frame and background. Suspicious object is detected using Histograms of Oriented Gradients (HOG) feature detection method. These features are then learned using the AdaBoost algorithm. Using data collected in our laboratory the system achieved an average accuracy of 85% for 3 types of objects while operating in real time.


Periodic Re-optimization based Dynamic Branch and Price Algorithm for Dynamic Multi-UAV Path Planning

Proceedings of the 2013 IEEE International Conference on Mechatronics and Automation(IEEE ICMA2013)

In this paper, a dynamic branch and price algorithm with a periodic re-optimization framework is proposed to solve the dynamic Multi-UAV path planning problem. By partitioning the planning horizon into a series of time slices, the dynamic problem is transformed into a series of static problems. We then use the adjusted branch and price algorithm to solve each static problem. The prominent characteristic of this algorithm is to improve the solving efficiency at each time slice by succeeding and adjusting the columns from the last time slice. According to the experimental results, the proposed dynamic branch and price algorithm with a periodic re-optimization framework can solve the test instances effectively.


Face Recognition Approach Based on Hyhrid Algorithm

Proceedings of the 2013 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing(NCSP'13)

Face recognition algorithm is a very promising technique in biometric authentication. However, the recognition precision can be affected by many factors, such as feature extraction method and classifier selection. In this paper, a novel algorithm for face recognition is presented. First we detect the face region using an improved AdaBoost algorithm. Second, we extract the appropriate features of the face by wavelet decomposition, and compose the face feature vectors as input to SVM. Third, we train the SVM model by the face feature vectors, and then use the trained SVM model to classify the human face. Finally, we present a face recognition system that can achieve high recognition precision and fast recognition speed in practice. In the training process, three different kernel functions are adopted: Radial basis function, Polynominal and Linear kernel function. Experimental results indicate that the proposed method can achieve recognition precision of 96.78 percent based on 96 persons in Ren-FEdb database.


Face Recognition Algorithm Using Wavelet Decomposition and Support Vector Machines

Proceedings of International Symposuim on OptoMechatronics Technologies(ISOT'12)

Face recognition algorithm is a very promising technique for biometric authentication. However, the recognition precision can be influenced by many factors. In this paper, a novel algorithm for face recognition is presented according to the advances of wavelet decomposition technique and Support Vector Machines (SVM) model. The extracted features from human images by wavelet decomposition are less sensitive to the facial expression variations. As a classifier, the SVM is provided with high generation performance without a transcendental knowledge. First, we detect the face region from the human face using an improved AdaBoost algorithm. Second, we extract the appropriate features of human face by wavelet decomposition, and compose the extracted features vectors to new feature vectors. Third, we train the SVM model by new face feature vectors, and then use the trained SVM model to classify the human face. In the training process, three different kernel functions are adopted: Linear kernel function, Polynomial kernel function and Radial basis function. Finally, we present a face recognition system that could achieve high recognition precision and fast recognition speed in practice. Experimental results indicate that the proposed method can achieve recognition precision of 96.78 percent based on 96 persons in Ren-FEdb database; from the results, our higher than that by SURF and other approaches.


Building Cracks Detection Using Unmanned Helicopter Images

Proceedings of 8th International Conference on Intelligent Unmanned Systems(ICIUS 2012)

Recently, numerous complicated high rise buildings are being constructed. However, it is difficult to inspect such buildings for structural damage regularly. In this research, we propose a system that can safely inspect such building using images captured by an unmanned helicopter.A panorama image was generated from the consecutive-numbered image acquired from the moving object, and a system which detects cracks in the image was developed. From now on, improvement in the accuracy of crack detection is aimed at.


Study on battery using konjac commercially available


Object Recognition from Aerial Rescue Robots

International Technical Conference on Circuits Systems Computers and Communications


Video Surveillance using Facial Features and Hand

Proceedings of World Academy of Science, Engineering and Technology(WASET2012)

In this work, we present a real time system for facial features detection and tracking and on hand gesture in image sequences. We are interested in developing a human tracking system that can improve human-computer interaction and benefit video surveillance problems by making it invariant to rotation, illumination and subject's movement. However, since human body and face movements are very complicated to detect and track, all available cues that can narrow the search space should be considered. This paper describes a novel strategy for both face tracking and facial feature detection. Face detection is important because it reduces the search space and consequently saves time for further face processing, e.g. recognition or transmission. Moreover, facial feature detection enables face normalization which leads to size invariant face recognition. The proposed face tracker resembles human perception in that, initially, it utilizes motion as the major cue and thereafter, searches for the eyes in the areas likely to contain human faces. The presence of a face is determined using an eye tracker. Eyes are important facial features due to their relatively constant interocular distance. In this work, efficiency improvement focuses on two points: reducing template matching area and speeding up the matching process. Our method initially detects two rough eye candidate regions using a feature based method. All other processes are thereafter performed inside the candidate regions. In addition, we can evaluate the size of eye template according to the size of the regions. Altogether, the proposed method combines the accuracy of template based methods and the efficiency of feature based methods in the visual spectrum. To prove the effectiveness of this approach, we performed comparative experiments using real video images. We achieved a real time detection accuracy of about 96.3%


Feature Extraction For Human Recognition Based On Bifurcation Points Using Genetic Algorithms

本論文では，遺伝的アルゴリズムを用いた分岐点に基づく人物認識のための特徴抽出手法を提案した．画像処理において，人物を認識する手法は様々開発されてきたが，人物はそれぞれ体形が異なり，さらに姿勢も変化するため，精度をあげることが難しい．そこで本手法では，交叉や突然変異などを繰り返しながら最適解を求める遺伝的アルゴリズムを用いることで人物認識のための特徴量を抽出する．


Tired State Recognition during Sports using Image Processing


A New Approach for Counting Passersby utilizing Space-time Images

ICDIMSP 2012 : International Conference on Digital Image and Multidimensional Signal Processing

Counting people and observing their movements are essential processes for security, organizational administration, and improving corporate business results. This paper presents amethod for automatically counting passersby using virtual-vertical measurement lines. Recognizing a passerby and generating space-time images are processed by animage sequence obtained from a USB camera. Space-time imagery represents recognizable regions surrounding each personwhich are processed fromlabeling-based segmentation. In this study, a space-time image represents the time as pixel-distance which is used to support the algorithm in order to achieve highly accurate counting. Human regions are detected by space colors based on template matching to select the optimal direction and speed. Whether the shape represents only one or two passersby can be ascertained using the relationship between the passerby speed and the human-pixel area. To verify the effectiveness of the proposed method, we performed experiments using a side view camera placed near the entrance. From the experiments, counting and direction accuracy were achieved 97%.


Reliable Human Recognition and Authentication using Retina Images

Proceedings of 18th Korea-Japan Joint Workshop on Frontiers of Computer Vision(FCV2012)

In this paper, we proposed a method of authenticating humans using retina images. In this work, we report on the preprocessing required before recognition ins performed. First, we extract only the blood vessel regions from a retina image using the HSV color space. The extracting method is the variable threshold method because of the varying color intensities in the image. After that, several methods including smoothing, sharpening, image composition, labeling and thinning are applied. We achieve about 98% blood vessel extraction rate using 20 retina images. We hope that the resulting image can then be used for feature extraction which can implement human authentication at high recognition rates.


An Eye Location Estimation Algorithm based on HSV Color Space and Template Matching

Proceedings of 18th Korea-Japan Joint Workshop on Frontiers of Computer Vision

An accurate eyes location method based on skin color using template matching is proposed in this paper. First the H channel in HSV spaces is used to characterize the colors range for skin detection, and roughly locating the face regions. Then an average synthetic eye template is used to locate the eyes. Experimental results indicate that the method based on HSV color space and template matching was proved accurate and fast. It is even unnecessary to do complex pre-processing and extra processing. The proposed method improves the locating speed and accuracy with better robustness. Experimental results also show that the proposed method could correctly locate the eye part in expressionless and in faces various expressions.


Abandoned Luggage Detection using a Dynamic Background Model and Earth Movers Distance


Robust Facial Features Tracking in Video Sequences using Efficient Template Matching

In this paper we proposed the method of detection and tracking of facial features like eyes, nose and mouth in image sequences using efficient template matching. Facial features tracking can improve human-computer interaction and benefit video surveillance. However, this is not a trivial task because of face size and orientation variations etc. This work presents a real time system for detection and tracking of facial features in video sequences. A skin-color model to segment face candidate regions in the image is used. The presence of absence of a face in each region is verified by means of an eye detector, base of an efficient template. Once a face is detected, the pupils, nostrils and lip corners are located and these facial features are tracked in the image sequence. The proposed system is efficient in tracking a mobile person in real time under varying conditions such as illumination, different movement and rotation.


A People Counting Method using Measurement Lines

It is important to count the number of people entering or leaving various business premises. This is because by knowing the number of people entering and leaving, strategies to increase sales or ease traffic congestion can easily be formulated. This work proposes extraction of people from a camera, and develops a method of counting them using multiple virtual measurement lines.


Proceedings of 2nd Asian Conference on Engineering Education (ACEE2011)

Airship Project is carried out by members of the part of ControlEngineering Laboratory and B1LABORATORY in The University ofTokushima. The first aim is to learn about how to develop the embeddedsystem based on a microcomputer. The second aim is to assemble theairship robot system as a test of the embedded system.To achieve these aims, we planned to participate the autonomousairship robot system contest (ESS Robot Challenge 2011). Forautonomous airship robot system, we adopt the augmented reality (AR)technology as positioning system.


Background Updating for Abandoned Luggage Detection at Train Stations


Gait Features Extraction Method using Image Processing

Proceedings of 17th Korea-Japan Joint Workshop on Frontiers of Computer Vision(FCV2011)

It is important to observe a person behavior in various scenes using a simple system. Therefore, in this paper, we propose a method to distinguish people by differences of the characteristics of walking.(gait) This method can acquire the characteristic of walker using the head, shoulder, hands and feet. Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method for Counting Passersby using Time-Space Image

Recently, there are many serious crimes happening in many institutions and commercial areas. Therefore, security and protection for those areas are needed. This paper proposes an automatic method for counting passersby using horizontal measurement line to solve this serious problem. In this paper, time and direction information are used to count passersby. Therefore, time-space image and measure the speed of each passerby with determination of their distance are applied. In our experiment, the camera is fixed on the front of the hall. A PC is connected to the camera with a frame rate 17 frame per second. Finally, our experimental results prove the effectiveness of our method.


Recognition of a person's state using FG Vision Sensor

It is effective to observe a person's state while protecting individual's information. FG Vision Sensor is able to acquire three-dimensional information and it can thus offer confidentiality. It is appropriate because the processing speed, when used in a monitoring system, is fast. In this research, we propose to recognize a person's state by using FG vision sensor.Some experimental results that indicate the effectiveness of the proposed method are also reported.


Facial Features-Based Method for Human Tracking

The detection and tracking of faces and facial features in video sequences is a fundamental and challenging problem in computer vision. This research area has many applications in face identification systems, model-based coding, gaze detection, human-computer interaction, teleconferencing, etc. This work presents a real time system for detection and tracking of facial features in video sequences. A skin-color model to segment face candidate regions in the image is used. The presence or absence of a face in each region is verified by means of an eye detector, based on an efficient template. Once a face is detected, the pupils, nostrils and lip corners are located and these facial features are tracked in the image sequence. The proposed system is efficient in tracking a mobile person in real time under varying conditions such as illumination, different movement and rotation.


Improving mobility for blind persons using video sunglasses

Proceedings of 17th Korea-Japan Joint Workshop on Frontiers of Computer Vision

Blind people navigate safely through a familiar room based on strong expectations about the location of objects. If something has been moved, added or removed, it can present a difficulty and potentially a danger. Human eyes are one of the most important body parts that help humans to understand and interact with their surroundings. Most learning and recognition of objects around us is accomplished using the eyes. Given the recent advancement of imagery systems and ever increasing processing power of microprocessors, a machine vision aiding system for the blind can be a reality. In the initial system we propose a system consisting of camera equipped sunglasses to capture the images and pattern recognition to automatically detect Braille tiles to aid mobility of blind persons. The information obtained is passed to the subject using audio messages.


Proceedings of 8th edition of France-Japan and 6th Europe-Asia Congress on Mechatronics

In this paper, we propose a method to realize virtual darts playing using image processing. A dart is composed of various colored parts, including the shaft and flights. Using these color features and extracting the necessary values while the dart is in motion, it is possible to perform trajectory calculations. These trajectory parameters can then be used to simulate virtual darts. Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method of Tracking Persons by Using the Internet Camera

Proceedings of 16th Korea-Japan Joint Workshop on Frontiers of Computer Vision(FCV2010)

Lately, the cases at various places by the suspicious individual occur successively.The network camera obtains it for a surveillance camera easily, and setting is possible. So, I usethe network camera which is way of neck possibility in this study and distinguish the person ofentrance and exit room and devise the technique that I chase while performing a way of neckfor a person of entering a room. Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method for Counting Passer-by In Public Life Space

To count the passer-by through the gate of buildings or roads in considered important for the office security or the marketing research. This paper proposed a simple system of measuring the number of passer-by. This system sets three switches, checks the state of the switch, and judge the movement direction. We can obtain the number of passers-by and each passing direction. Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method of Detection of Moving Objects by Using a Surveillance Camera on the Campus

Its important to know traffic census. This report is concerning the measurement of the number of person, bicycle or car. In this research, it comes to be able to do the traffic census more easily and even if the person is not employed. Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method for Counting Passerby by Length and Breadth Measurement Line

In this paper, we propose a method of counting passerby with a camera. In counting passerby with a camera, the processing pursued to the person's movement is necessary, because the person cannot be correctly extracted by noise. In this paper, by using space-time image made by length and breadth measurement line, identification of the person and counting passerby. Some experimental results that indicate the effectiveness of the proposed method are also reported.


Video Surveillance using Facial Features

The detection and tracking of faces and facial features in video sequences is a fundamental and challenging problem in computer vision. This research area has many applications in face identification systems, model-based coding, gaze detection, human-computer interaction, teleconferencing, etc. This work presents a real time system for detection and tracking of facial features in video sequences. A skin-color model to segment facecandidate regions in the image is used. The presence or absence of a face in each region is verified by means of an eye detector, based on an efficient template. Once a face is detected, the pupils, nostrils and lip corners are located and these facial features are tracked in the image sequence. The proposed system is an efficient to track the moving Human in real time under some kinds of difficulties such as varying illumination, different movement and rotation.


A Framework for Human Tracking using Kalman Filter and Fast Mean Shift Algorithms

Proceedings of Second IEEE International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences

) The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human tracking. It includes a combination of Kalman filter and fast mean shift algorithm. Kalman prediction is measurement follower. It may be misled bywrong measurement. The search for solution is guided by a fast mean shift procedure. It is used to locate densitiesextrema, which gives clue that whether Kalman predictionis right or it is misled by wrong measurement. Tracking results are demonstrated for crowded scenes andevaluation of the proposed tracking framework ispresented.


A General Framework for Multi-Human Tracking

Proceedings of International Workshop on Computer Science and Engineering 2009(WCSE2009)

The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human tracking. It includes a combination of Kalman filter and fast mean shift algorithm. Kalman prediction is measurement follower. It may be misled bywrong measurement. The search for solution is guided by a fast mean shift procedure. It is used to locate densitiesextrema, which gives clue that whether Kalman predictionis right or it is misled by wrong measurement. Tracking results are demonstrated for crowded scenes andevaluation of the proposed tracking framework ispresented.


Simple Human Observation System by Information Obtained from Internet Cameras

Proceedings of The 15th Korea-Japan joint Workshop on Computer Vision(FCV2009)

In this paper, we propose the method of observing human behavior by using three-dimensional information acquired from Internet cameras. The image acquired by the Internet camera has only coarse sampling. In this method, the number of people, a position, and height are measured with reducing the fluency of course sample.Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method for Counting Passerby by Accumulated Subtraction Images

Proceedings of The 14th Korea-Japan joint Workshop on Computer Vision(FCV2009)

In this paper, we propose a method of tracking and counting passerby with a camera. In counting passerby with a camera, the processing pursued to the person's movement is necessary,because the person cannot be correctly extracted by noise. In this paper, by using simpleaccumulated Subtraction image, tracks of the passerby person can be requested, and passerby can be counted without the influence of the noise and the pursuit processing of the person.Some experimental results that indicate the effectiveness of the proposed method are also reported.


Object Detection and Tracking Using Kalman Filter and Fast Mean Shift Algorithm

Proceedings of the Fourth International Conference on Computer Vision Theory and Applications

Object detection in videos involves verifying the presence of an object in image sequences and possibly locating it precisely for recognition. Object tracking is to monitor an objects spatial and temporal changes during a video sequence, including its presence, position, size, shape, etc. These two processes are closely related because tracking usually starts with detecting objects, while detecting an object repeatedly in subsequent image sequence is often necessary to help and verify tracking. In this paper, a novel approach is being presented for object tracking. It includes combination of Kalman filter and fast mean shift algorithm. Kalman prediction is measurement follower. It may be misled by wrong measurement. In order to cater it, fast mean shift algorithm is used. It is used to locate densities extrema, which gives clue that whether Kalman prediction is right or it is misled by wrong measurement. In case of wrong prediction, it is corrected with the help of densities extrema in the scene. The proposed approach has the robust ability to track the moving object in the consecutive frames under some kinds of difficulties such as rapid appearance changes caused by image noise, illumination changes, and cluttered background.


Tracking Object using Kalman Filter and Fast Mean Shift Algorithm

Proceedings of the International Workshop on Vision, Communications and Circuits(IWVCC'08)


A Method of Observing Human Behavior with Multi Internet Cameras

Proceedings of The 14th Korea-Japan joint Workshop on Computer Vision(FCV2008)

In this paper, we propose the method of observing human behavior by using three-dimensional information acquired from multi network cameras. The image acquired by the network camera has only coarse sampling. In this method, the number of people, a position, posture, height and movement are measured with reducing the fluency of coarse sample. Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method for Observing Behavior of people at the Entrance

In this paper, we proposes a method for observing person at the entrance by using the surveillance camera. The sequence image is acquired from the surveillance camera. The movement and the posture of the person are extracted from obtained image. A suspicious person is recognized by eight features.Some experimental results that indicate the effectiveness of the proposed method are also reported.


A Method for Counting Multidirection Passerby by Using Circular Space-Time Image

In this paper, we propose a method of counting multidirection passerby with a camera. By using this method, multidirection passerby can be counted at the wide place forcongestion reducing, efficient promotion of the institution management, sales improvement.In this method, a circular measurment line is set on a sequence of the background subtraction images.All pixels on this line is transformed to the space-time image.The number of passer-by can be counted by using this space-time image. But the direction information of passer-by cannot be obtainedfrom this space-time image. Therefore, two circular measurment lines are set on a sequenceof the background subtraction images. Two space-time images are generated from the outside line and the inside line. The directions of passer-by can be obtained by detecting which line passer-by passed previously.


Evaluation of Awa-Dance Skill by Stereo Color Motion Capture

Proceedings of The 13th Korea-Japan joint Workshop on Computer Vision(FCV2007)

In this paper, the authors propose a method for sensing the movement of the Awa-Odori dance which is traditional culture of Tokushima prefecture in Japan. In this system, the skill of Awa-Odori dance is evaluated by using 3D data obtained from low cost motion capture system. We evaluated our method by using the image squences of the dance of the experience person and the beginner person of the Awa-Odori.


A Method ofr observing Behavior of People by Bright-spots Matrix Projection

Proceedings of Second Asia International Symposium on Mechatronics(AISM2006)

Information obtained by using the monaural camera is 2D data. Therefore, it is difficult to get information of the persons position, direction, and shape. Then, the sensorwhich is able to obtain 3D data is required. In this paper, we propose a method of observingthe position, direction and shape of people by using 3D information. In this reserch, peoples3D information is acquired using FG vision sensor which has been developed by the authors. Position information, direction information and height information are detected by extracteda cylinder from 3D data. Im this process, Hough transform is used to detect position, X-axisand Y-axis of ellipse of a cylinder. The tracking is carried out using the position and the heightinformation in realtime.


Observing Behavior of People by FG Vision Sensor

Proceedings of The 12th Korea-Japan joint Workshop on Computer Vision(FCV2006)

Information obtained by using the monaural camera is 2D data. Therefore, it is difficult to get information of the persons position, direction, and shape. Then, the sensor which is able to obtain 3D data is required. In this paper, we propose a method of observing the position, direction and shape of people by using 3D information. In this reserch, peoples 3D information is acquired using FG vision sensor which has been developed by the authors. Position information, direction information and height information are detected from 3D data. The tracking is carried out using the position and the height information in realtime.


Recognition of Small Harmful Insects Using Internet Camera

In this paper, we propose a method of surveillance of the plant growth using the camera image. This method is able to observe the condition of raising the plant in the greenhouse. The plate which is known as HORIBA is prepared for extracting harmful insect. The image of HORIBA is obtained by the camera and used for processing. The resolution of the image is 1280×960. In first process, region of the harmful insect (fly) is extracted from HORIBA by using color information. In next process the template matching is performed to examine the correlation of shape in four different angles. 16 kinds of results are obtained by four different templates. The sum logical of the results is calculated for estimation. In addition, the experimental results are shown in this paper.


A Method of Detecting Gender by Smiling Facial Image

In this paper, the authors propose a method of men and women discrimination by extracting difference of the facial expression change from color facial images. Now, there are a lot of methods of the automatic recognition of the individual using a motion facial image or a still facial image in the field of image processing. However, it is very difficult to discriminate gender under the influence of the hairstyle and clothes, etc. Therefore, we propose the method which is not affected by personality such as size and position of facial parts by paying attention to a change of an expression. In this paper, it experimented for the laughing expression and smile expression, and good results were provided for discriminating gender.


Surveillance of the plant growth using the camera image


Discrimination of gender using facial image with expression change

By carrying out marketing research, the managers of large-sized department srores or small convenience stores obtain the information such as ratio of men and women of visitors and an age group, and improve their management plan. However, these works are carried out in the manual operations, and it becomes a big burden to small stores. In this paper, the authors propose a method of men and women discrimination by extracting difference of the facial expression change from color facial images. Now, there are a lot of methods of the automatic recognition of the individual using a motion facial image or a still facial image in the field of image processing. However, it is very difficult to discriminate gender under the influence of the hairstyle and clothes, etc. Therefore, we propose the method which is not affected by personality such as size and position of facial parts by paying attention to a change of an expression. In this method, it is necessary to obtain two facial images with an expression and an expressionless. First, a region of facial surface and the regions of facial parts such as eyes, nose, and mouth are extracted in the facial image with color information of hue and saturation in HSV color system and emphasized edge information. Next, the features are extracted by calculating the rate of the change of each facial part generated by an expression change. In the last step, the values of those features are compared between the input data and the database, and the gender is discriminated. In this paper, it experimented for the laughing expression and smile expression, and good results were provided for discriminating gender.


Recognition of a Smoke Region Using Fractal Cording

Proceedings of The 10th Korea-Japan joint Workshop on Computer Vision(FCV2004)

Damage due to fire can be minimized by discovering fires early. Fires produce smoke as well as flames, so detecting smoke from data like surveillance camera images data can make it easier to discover fires early. However, in attempting to discover fires at locations which are hard to see with the human eye, as cases like forest fires, we are faced with a problem in that smoke does not have a determinate form in camera images. It has a pattern similar to features like clouds, sky and forests, and thus is difficult to detect with processing approaches like simple background subtraction or pattern matching. So this paper proposes a technique for extracting smoke regions from an image using fractal encoding concepts. We were led to this idea by noticing that smoke shapes have the property of self-similarity, and here we attempt to extract smoke regions by discovering the distinguishing features of smoke regions in the code produced by fractal encoding.


Extraction of a Smoke Region Using Fractal Cording

Proceedings of International Symposium on Communications and Information Technologies 2004(ISCIT2004)

Damage due to fire can be minimized by discovering fires early. Fires produce smoke as well as flames, so detecting smoke from data like surveillance camera images data can make it easier to discover fires early. However, in attempting to discover fires at locations which are hard to see with the human eye, as cases like forest fires, we are faced with a problem in that smoke does not have a determinate form in camera images. It has a pattern similar to features like clouds, sky and forests, and thus is difficult to detect with processing approaches like simple background subtraction or pattern matching. So this paper proposes a technique for extracting smoke regions from an image using fractal encoding concepts. We were led to this idea by noticing that smoke shapes have the property of self-similarity, and here we attempt to extract smoke regions by discovering the distinguishing features of smoke regions in the code produced by fractal encoding of an image.


Observing Passing People by Using Fiber Grating Vision Sensor

Proceedings of the 2004 IEEE Conference on Control Applications/International Symposium on Intelligent Control/International Symposium on Computer Aided Control Systems Design

Information obtained by using the monaural camera is 2D data. Therefore, it is difficult to get information of the persons position, direction, and shape. Then, the sensor which is able to obtain 3D data is required. In this paper, we propose a method of observing the position, direction and shape of people by using 3D information. In this research, peoples 3D information is acquired using FG vision sensor which has been developed by the authors. Position information, direction information and height information are detected by extracted a cylinder from 3D data. In this process, Hough transform is used to detect position, X-axis and Y-axis of ellipse of a cylinder. The tracking is carried out using the position and the height information in real time.


A Method for Observating People by using FG Vision Sensor


Distance and Velocity Measuring Method Using Optical Flow and Stereo Method

Proceedings of the 10th Korea-Japan Joint Workshop on Frontier of Computer Vision(FCV2004)

In this paper, we proposed a new method for measuring absolute distance and absolute velocity by using optical flow and stereo method. In order to work autonomously for robot keeping up with various situations in real environment, it is necessary for robot to recognize the three-dimensional information of environment and motion information. Up to now, many methods such as light projection method, stereo method and monocular vison method have been proposed for obtaining three-dimensional information. These methods can be applied to measure the distance from camera to object, but cannot extract motion information of objects. As one of the techniques for extraction motion information of moving objects, there is optical flow method obtained from image sequence using monocular camera. This method can estimate the distance and motion information of object. However, the information measured by using the optical flow is the relative distance and the relative velocity. So, by combining with the absolute distance of only one point by using stereo method and optical flow, our method can measure absolute distance and absolute velocity.


Quality Evaluation Method of the Weld Bead

Proceedings of 4th Asia-Europe Cognress on Mechatronics

The welding is the important basic materials joining technology. The quality of welding is affected by the skill of the person. Therefore, the welding skill qualifying test is held in each prefecture. As nowadays, the evaluation of the welding is carried out by human, the evaluation is different even for the same work from different judges and the judges themselves standard. There are some problems in objectivity and reproducibility of the evaluation. In this paper, we propose the evaluation of the weld bead quantitatively by using three-dimensional data obtained by the slit light projecting method.


The Identification using the Wavelet Transform Face Image

The purpose of this study is for the individual identification using the wavelet transform face image. It is possible for the wavelet transformation to catch the signal from time and frequency characteristic, so it can reduce the influence of lighting and compensate the position. This technique is verified by carrying out discrimination experiment.


Texture Image Segmentation by using Wavelet Transform and Pyramid Linking Method

Proceedings of the 9th Korea-Japan Workshop on Frontiers of Computer Vision(FCV2003)

In recent studies on image analysis, an increasing effort has been carried out in the area of wavelet transform techniques for the texture image segmentation and classification. This method is that an effective texture image segmentation algorithm by using wavelet transform and neural network. The basic idea of proposed method is first decomposing an original image into several filtered images which contain information in different orientation and frequency ranges, and these filtered images are of the same size as the original images. The texture features are extracted by calculating the energy measure by wavelet coefficient and two dimensional autoregressive model of the small window in the filtered sub images. Then, the segmentation number automatically decided by using Kohonens self-organizing neural network and pyramid linking method. The bandpass neural network is used for the pyramid linking method. In order to obtain high accurate segmentation method. In order to obtain high accurate segmentation, we propose the segmentation method a pixel precision. Finally, the effectiveness of the proposal technique is verified by several kinds of segmentation results.


Three-Dimensional Modeling System with High Spatial Resolution Using Movable Color CCD

The development of the system, which can model the three-dimensional shape such as the art object accurately under the non-improvement environment, it desired. As techniques of three-dimensional information acquisition, there are light projection method, stereo method, shape from focus method and so on. In the light projection method there is a case in which it cannot use under natural light and special color of the object, for example black. In the stereo method there is the surface pattern, which the corresponding point search is difficult. In our laboratory, we have developed three-dimensional information acquisition system in order to use shape from focus method, which composed of the movable CCD and fixed lens. This system is different from focus method, which composed of the movable CCD and fixed lens. This system is different from traditional one with fixed CCD and movable lens. When using shape from focus method, the size of view field acquired images. Our system has the characteristic that the difference between the sizes of view field acquired from image sequence can be adjusted easily. In this paper, we proposed the method of accurate distance measurement by improving this system and the method for modeling the three-dimensional shape.


Detecting of One's Eye from Facial Image by Using Genetic Algorithm

Proceedings of International Technical Conference on Circuits/Systems, Computers and Communications(ITC-CSCC2001)

If ones eye can be detected by camera, it is applied to observe action of human, and to check looking aside when we are driving. But there is no effective method now, because of changing condition of light and direction of face on image. Therefore in this paper, we propose the method that extract region of eyes out of facial image by genetic algorithm and detect ones eye. In this method, it is influenced neither situation nor expression and direction of face by devising string and fitness.


Three Dimensional Measurement Using Color Image and Movable CCD System

The paper deals with a new distance measurement method of color images by using an RGB color histogram. We measure the distance based on the principle of Depth-from-focus. It needs to detect focal position among many images with different focusing position. Our method is based that the more focal area has the less color frequency. By this method, we detect the focal area without using spatial frequency as conventional methods. The validity of our method is verified by some experimental results.


A Texture Analysis Method by Using Local Binary Pattern

Proceedings of the 7Th Kore-Japan Joint Workshop on Computer VIsion(FCV2001)

In this paper, we present a new analytic technique to express the quality of an image which contains several regions generated by rotating texture of same quality with different rotation angles. To analyze, we pay attention to Local Binary Pattern which can extract the feature of texture and rotation invariant feature based on Local Binary pattern, and propose the method which detects the angle of the region which an angle is different with same quality texture. In experiment, detailed analytic result of the test image is shown.


Personal Identification based on Handprint View Image by Using Color CCD Camera

Proceedings of the Sixth International Conference Control, Automation, Robotics and Vision(ICCARV200)

n this paper, the authors propose a method of identifying individuals using the handprint view image by obtained from the color CCD camera. Sophisticated technology information-driven society need to be considerably improved advanced security. Because of now personal identification is not adequate security countermeasures. For instance, to take an illustration in such cases do not reveal your personal identification number to anyone. It is able to unlawful access t o a computer. In this paper, we propose a personal identification method based on hand shape and palm print by obtained no contact with screen panel. In this method, identification process is carried out by the method based on the subspace method by using 19 features from the hand shape and palm print image. Handprint and palm print view image is obtained by using color CCD camera. This work is effective personal identification method.


Counting Passers by Using Angled Dual Line images

Proceedings of the Sixth International Conference Control, Automation, Robotics and Vision(ICCARV2000)

The attempts to count the passing people by the image processing have been made some time ago. But the conventional methods could not count the passing people accurately unless there were few of the passing people through the gate at one time. In this paper, we propose an automatic method of counting the passing people by using the angled measurement line. In proposed method, the camera is hung from the ceiling of the gate and the optical axis of the camera is set up so that the passing people could he observed from just overhead. In this system arrangement, if there are crod people in the gate, then the data of the passing people are not overlapped each other on the obtained images. In addition, by using the color CCD camera, the human region and road region on the obtained images are able to he segmented accurately. In this paper, we show some experimental results obtained by using a simple experimental system to verify effectiveness of the proposed method.


Focused Edge Detection Using Color Histogram

Proceedings of 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation(IECON2000)

This paper deals with a new edge detection algorithm of color images by using an RGB color histogram. From the investigation for edge characteristics based on the histogram, it became clear that the edge part has large color variations influenced by noise and is the minor area in the RGB color histogram. In order to detect this minor area stably, we propose a new method by which we can retrieve the low-bit areas from the image constructed by summing up the multi-gray histogram images which are obtained from the RGB color histogram. The validity of the proposed method is verified by some examples of applications to real scenes. The proposed method has advantages in that edge detection is not affected by gradient magnitude and features of curved surfaces can be selectively detected by variable detection parameters. Because of the low cost of calculation, we can easily implement this algorithm within an image frame accumulation process, performed before objective image processing.


Fingerprint Identification using Fractal Coding

Proceddings of the Nonlinear Theory and Its Applications(NOLTA'99)

In this paper, we propose a novel method of identification of fingerprint by using fractal coding. Automatic identification of person is one of important techniques for information and security systems. Such features bases on persons physiological or behavioral characteristics are called biometrics. Fingerprint is the most suitable information as a biometric; everyone has own immutable coding technique is applied to data compression of images. We pay attentions to the basic concept of this coding method - self-similar property in a fingerprint. We develop an identification system using the compressed data of fingerprint image. We can do identifying process for compensation image by using fractal coding, and it is abstract for feature value by compressed data. Practical experiments of fingerprint extracted feature finding from compressed data are performed and experimental results are presented.


An Improvement of Image Segmentation by using Fractal Coding

Proceedings of the Nonlinear Theory and Its Applications(NOLTA'99)

This paper presents improvements for conventional image segmentation algorithm by using fractal coding. The compressed data with fractal coding is a set of parameters of affine mapping. This algorithm utilizes this compressed data to split an original image into some segments which have different feature. Image segmentation can be achieved by calculation for basins of attractions in the dynamical system computing the inverse affine mapping. The higher quality segmentation image can be obtained by adding a small perturbation to inverse affine mappings. This note describes the proposed method and shows some segmentat8oin results by using this algorithm.


Edge Characteristics of Color Images and Edge Detection Using Color Histogram

Proceedings of 4th International Conference on Advances in Pattern Recognition and Digital Techniques(ICAPRDT'99)

This paper deals with a new edge detection algorithm of color images by using an RGB color histogram. From the investigation for edge characteristics based on the histogram, it became clear that the edge part has large color variations influenced by noise and is the minor area in the RGB color histogram. In order to detect this minor area stably, we propose a new method by which we can retrieve the low-bit areas from the image constructed by summing up the multi-gray histogram images which are obtained from the RGB color historagm. The validity of the proposed method is verified by some examples of applications to real scenes. The proposed method has advantages in that edge detection is not affected by gradient magnitude and features of curved surfaces can be selectively detected by variable detection parameters. Because of low cost of calculation, we can easily implement this algorithm within an image frame accumulation process, performed before objective image processing.


An Individual Identification by Using an Angled Facial Data

Proceedings of the 25th Annual International Conference of the IEEE Industrial Electronics Society(IECON'99)

In this paper, the authors propose a method of identifying individuals using the angled facial image obtained from the CCD camera. We think that we can obtain the more effective data for identifying the faces by setting the CCD camera at an angle to the faces. When the CCD camera like this is set, we think that the effective information is able to be obtained from the large region of one side of the faces, the information of nose height which is one of three dimensional facial information and the cheek undulation which is part of the outline of their profiles. Before the identification of the face is carried out with the use of this angled image data, the calibrations relative to the positions, the scales and the directions of the faces of the subjects at the time the data were obtained. The input data for identification is composed of the following; the edge image of the certain region around the right eye; the gray image of the certain region around the mouth; the gray image of the certain region around the mouth; the shape of the nose; and the shape of the outline of the angled face. The experiments using the experimental system are performed to demonstrate of the efficacy of this method and the experimental results are shown.


A Counting Method of the Number of Passing People Using a Stereo Camera

The attempts to count the passing people by the image processing have been made some time ago. But the conventional methods could not count the passing people accurately unless there were very few of the passing people though the gate at one time. In this paper, we propose that passing people be accurately counted using images obtained by a stereo camera. In proposed method, the stereo camera is hung from the ceiling of the gate and the optical axis of the camera is set up so that the passing people could be observed from just overhead. In this system arrangement, if there are cored people in the gate, then the data of the passing people are not overlapped each other on the obtained images. In addition by using the stereo camera, the human region and road region on the obtained images are able to be segmented accurately. In this paper, we show some experimental results obtained by using a simple experimental system to verify effectiveness of the proposed method.


A Method of Counting the Passing People by Using the Stereo Images

Proceedings of the 1999 IEEE International Conference on Image Processing(ICIP'99)


Modeling of 3-D object by using distance measurement system with movable CCD

Proceedings of 5th International Conference on Quality Control by Artificial Vision(QCAV99)

In this paper, we propose a new modeling method of 3-D object by using distance information. The distance information is measured by using the distance measurement system which uses a monocular camera with a fixed lens and movable CCD. Our system is constructed from rotatable stage, on which an object is located, and distance measurement system. We perform the modeling of 3-D object by using the distance information from some viewpoints. In the case of unknown rotational angle, it is necessary to find that angle. So, we propose a method to estimate it. The validity of this method is verified by some numerical examples.


A Range Finder by Using a Rotary Cubic Mirror

Proceedings of IAPR WORKSHOP on Machine Vision Applications(MVA'98)

The slit light scanning method is a conventional method of range finder. But according to this method, it is impossible to measure the three dimensional shape when the object is too large, because camera is fixed against the observation field. In this paper, we propose a new active range finder with a rotary cubic mirror to solve these problems. In this sensing system, slit light and view of camera are moved to the same direction simultaneously by using a rotary cubic mirror. This method is able to obtain the slit light image which dose not include distortion. On the other hand in the proposed sensing system, the image of slit is projected on near the center of the image plane all the time by moving the slit light and the view of camera simultaneously. The experiments were performed to demonstrate the efficacy of this sensor by using this system. As a result, the proposed method can measure the three dimensional position of the object and effectiveness was shown.


A Method of Counting the Passing People by Using the Method of the Template Matching

The attempts to count the passing people by the image processing have been made some time ago. But the conventional methods could not count the passing people accurately unless there were very few of the passing people through the gate at one time. In this paper, we propose an automatic method of counting the passing people by using the method of the template matching process. In proposed method, the camera is hung from the ceiling of the gate and the optical axis of the camera is set up so that the passing people could be observed from just overhead. In this system arrangement, if there are crowd people in the gate, then the data of the passing people are not overlapped each other on the obtained images. In addition, by using the color CCD camera, the human region and road region on the obtained images are able to be segmented accurately. In this paper, we show some experimental results obtained by using a simple experimental system to verify effectiveness of the proposed method.


Counting Method of the Number of a Crowd of People Using a Color Camera

Proceedings of the 4th International Conference on Quality Control by Artificial Vision(QCAV'98)


Three Dimensional Vision Sensor by Using Swinging Cubic Mirror

Proceedings of the 4th Korea-Japan Joint Workshop on Computer Vision(FCV98)

Slit light scanning method 1s a conventional method of range finder. But according to this method, camera is fixed toward the observation field, it is impossible to measure the distance when the object is larger than the field of view. And it cannot measure the distance correctly when the object exists near the edge of the observation field. Because slit light is projected near the edge of image plane, an image with distortion is obtained. In this paper, we propose a new active range finder to solve these problems. Laser projector and CCD camera are opposite from each other on the optical axis, and set the cubic mirror between them. So due to swing the cube, slit light and view of camera are moved to the same direction simultaneously with no need a strict calibration. This sensor has three advantages; the image of slit light without distortion; wider observation field; a simple system composition. The experiments are performed to demonstrate the efficacy of this sensor. As a result, the proposed method can measure the 3D position of the object and effectiveness was shown.


An Automatic Distance Measurement System by Using Monocula Camera with Movable CCD

Proceedings of 4th Japan-Korea Joint Workshop on Computer Vision(FCV98)

We propose a new method that is able to measure a distance accuracy by using a monocular camera with fixed lens and movable CCD. For the image sequence obtained by moving CCD along to the optical axis at constant intervals, we extract some images with most focused small area corresponding to each part in field-of-view of camera. Then it is important how to select the focused small area, so we propose a method to do it accurately. Our method has an advantage that it is easy to correct the scale and location change by movable CCD. We developed the automatic distance measurement system. As the applications using this system, we suggested how to obtain the all focused image and how to correct the distortion of the image with curve surface. The validity of this method is verified in experiment results.


A Distance Measurement Method available to Thexture Surface by Using Complex-Log Mapping

Proceedings of the 23rd Annual International Conference of the IEEE Industrial Electronics Society(IECON97)

Abstract- In this paper, we proposed a method to measure the distance from the camera to an object's surface with arbitrary texture pattern. The method uses two images which are taken at two camera positions while moving the camera along its optical axis. The distance between the two camera positions is assumed to be known. The distance from the camera to the object is computed by calculating the ratio between the sizes of the object projected on the two images. To calculate the ratio, Complex-Log Mapping is applied according to the fact that the two images have concentric circles features.


Improvement of Accuracy for a Distance Measurement Method by Movement of CCD

Proceedings of the 2nd Japan-China Symposium on Mechatronics

We propose a new method that is able to measure distance accuracy by using a monocular camera with fixed lens and movable CCD. For the image sequence obtained by moving CCD along to the optical axis at constant intervals, we extract some images with most focused small area corresponding to each part in field-of-view of camera. Then it is important how to select the focused small area, so we propose a method to do it accurately. Our method has an advantage that it is easy to correct the scale and location change by movable CCD. The validity of this method is verified in experiment results.


In this paper, we propose an active 3D sensor. A feature of this sensor is its characteristic optical arrangement. The CCD camera and the slit projector are set on opposite to each other on the optical axis, and the cube is set between them. The surface of the cube is overlapped by the mirrors, and the cube is rotated by the stepping motor. Therefore, slit light and view of camera are moving same direction simultaneously, and image of slit are always projected on near the center of image plane. For the reason stated above, this sensor has 3 points of advantage: the image of slit light without distortion; wider observation field than the conventional light cutting method of simple system composition, The experiments using the experimental system are performed to demonstrate the efficacy of this method and the experimental results are shown.


A Method of Distance Measurement Using Monocular Camera

Proceedings of the 36th SICE Annual Conference International Session

In this paper, we propose the method to measure the distance to the surface with any figures. The method uses two images, one is taken at a camera point and the other is taken at the point where the camera is moved along the optical axis. The distance is calculated from the ratio between each size of an object projected on two images. From the fact that the pair of images has concentric circles features, the ratio is obtained by using Complex-Log Mapping. This method can calculate the distance to the surface with texture feature or not.


Improvement of Accuracy for Distance Measurement Method by using Movable CCD

The Society of Instrument and Control Engineers

We propose a method that measures a distance by using a camera with fixed lens and movable CCD. For the image sequence obtained by moving CCD along to the optical axis at constant intervals, we extract some images with focused small area corresponding to each part in the range of camera. Then it is important how to select the focused small area, so we propose a method to do it accurately. Our method has an advantage that it is easy to correct the size change by movable CCD. The validity of this method is verified in experiment results.


A Method of Distance Measurement Using a Monocular Camera with Movable CCD

Proceedings of 3th Japan-Korea Joint Workshop on Computer Vision(FCV97)

We propose a new method that is able to measure a distance accurately by using a monocular camera with fixed lens and movable CCD. For the image sequence obtained by moving CCD along to the optical axis at constant intervals, we extract some images with most focused small area corresponding to each part in field-of-view of camera. Then it is important how to select the focused small area, so we propose a method to do it accurately. Our method has a advantage that it is easy to correct the scale and location change by movable CCD. The validity of this method is verified in experiment results.


An Automatic Method of Counting the Passing People through the Gate by using the Two Space-time Images

Proceedings of IAPR WORKSHOP on Machine Vision Applications(MVA96)

In this paper, an automatic method of counting the passing people through the gate by using two space-time images is proposed. In the proposed method, the images are obtained in series by using a camera which is hung straight from the ceiling of the gate, so that the data of the passing people are not overlapped each other in the images. First, a space-time image which includes the data of the passing people over the measurement line is generated. But in this system arrangement, each moving direction of the passing people cannot be recognized from one space-time image. Therefore, two measurement lines are set on the inside and outside of the gate and two space-time images are generated. By detecting which line the person passes early, each moving direction is recognized. Finally, the incoming and outgoing persons could be measured by counting the people data on two space-time images of each moving direction.


Motion Analysis of Echocardiograph Using Optical Flow Method

Proceedings of 1996 IEEE International Conference on Systems, Man and Cybernetics(SMC96)

A gradient-based method is applied to analyze two echocardiograph sequences' velocity field. The method assumes local spatial constancy of the optical flow and uses a weighted least-squares minimization to determine the optical flow. A hierarchical improvement to the method is proposed to solve the problems of motion blur and sensitivity to noise. Experimental results show that both the implemented method and the improvement to it are available to obtain global quality evaluation of the velocity field of the echocardiograph sequences.


A Method For Identifying Individuals Using Angled Facial Data Obtained By Bright-spots Matrix Projection

Proceedings of IEEE Instrumentation and Measurement Technology Conference '94

We have already proposed a method for identifying human faces using the three dimensional facial data obtained by setting the fiber grating vision sensor in front of the faces. But in the previous method, there are some problems that these facial data include redundant information because of the bilateral symmetry of the human faces, and in some case, the data behind the nose can't be obtained. In this paper, the authors describe a method for identifying individuals using the angled facial data obtained from the fiber grating vision sensor. We think that we can obtain the more effective data for identifying the faces by setting the fiber grating vision sensor at an angle to the faces. Because we can obtain the effective information from the large region of one side of the faces when we set the sensor like this. In this method, the fiber grating vision sensor which has been developed by the authors, is employed for the three dimensional shape of the faces. Before identifying the facial data, it is necessary to calibrate the position and direction of the facial data. In this method, a set of the directions of normal vectors at data points on the facial surface is obtained, and calibrations are carried out in accordance with the extend of errors in the sets. To identify the human faces, a multi-layered neural network is used in which the inputs are two component values of normal vector on the facial surface. The experiments using the experimental system are performed to demonstrate the efficacy of this method and the experimental results are shown.


An Identification of Human Faces Using Bright-spots Matrix Projection

Proceedings of International Joint Conference on Neural Networks '93

In this paper, the authors describe a method for the identification of human faces. In this method, the fiber grating(FG) vision sensor which has been developed by the authors is employed for the three dimensional shape of the faces. Before the identification of the face using the three dimensional shape of the face, it is necessary to calibrate the position and direction of the facial data. In this method, a set of the directions of normal vectors at data points in the facial surface is obtained, and calibrations are carried out in accordance with the extend of errors in the sets. To identify human faces, a multilayered neural network is used in which the inputs are two component values of normal vector at data spot in the facial surface. An experiments using an experimental system is performed to demonstrate the efficacy of this method and the experimental results are shown.


An Automatic System for High Speed 3-D Objects Recognition using Fiber Grating Vison Sensor

Proceedings of IMACS/SICE International Symposium on Robotics, Mechatronics and Manufacturing Systems '92(IMACS'92)

n this paper, we describe an automatic system for high speed three dimensional objects recognition using the fiber grating(FG) vision sensor which has been developed by our group. This sensor is so small and light that it could be installed on a robot hand directly. First, in order to recognize three dimensional objects, we obtain the range data by using this vision sensor. We recognize the size and position of spherical objects as three dimensional objects which are placed in disorder.