{"title":"Real-time human motion analysis and IK-based human figure control","authors":"S. Yonemoto, Daisaku Arita, R. Taniguchi","doi":"10.1109/HUMO.2000.897385","DOIUrl":null,"url":null,"abstract":"The paper presents real-time human motion analysis based on real-time inverse kinematics. Our purpose is to realize a mechanism of human-machine interaction via human gestures, and, as a first step, we have developed a computer-vision-based human motion analysis system. In general, man-machine \"smart\" interaction requires a real-time human full-body motion capturing system without special devices or markers. However, since such a vision-based human motion capturing system is essentially unstable and can only acquire partial information because of self-occlusion, we have to introduce a robust pose estimation strategy, or an appropriate human motion synthesis based on motion filtering. To solve this problem, we have developed a method based on inverse kinematics, which can estimate human postures with limited perceptual cues such as positions of a head, hands and feet. We outline a real-time and on-line human motion capture system and demonstrate a simple interaction system based on the motion capture system.","PeriodicalId":384462,"journal":{"name":"Proceedings Workshop on Human Motion","volume":"122 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Workshop on Human Motion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HUMO.2000.897385","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 36
Abstract
The paper presents real-time human motion analysis based on real-time inverse kinematics. Our purpose is to realize a mechanism of human-machine interaction via human gestures, and, as a first step, we have developed a computer-vision-based human motion analysis system. In general, man-machine "smart" interaction requires a real-time human full-body motion capturing system without special devices or markers. However, since such a vision-based human motion capturing system is essentially unstable and can only acquire partial information because of self-occlusion, we have to introduce a robust pose estimation strategy, or an appropriate human motion synthesis based on motion filtering. To solve this problem, we have developed a method based on inverse kinematics, which can estimate human postures with limited perceptual cues such as positions of a head, hands and feet. We outline a real-time and on-line human motion capture system and demonstrate a simple interaction system based on the motion capture system.