A 3D predictive visual tracker for tracking multiple moving objects with a stereo vision system

Yi Ping Hung, Cheng Yuan Tang, Sheng Wen Shih, Zen Chen, Wei Song Lin

研究成果: 書貢獻/報告類型會議貢獻

1 引文 斯高帕斯(Scopus)

摘要

This paper presents a 3D feature-based visual tracker for tracking multiple moving objects by using a predictor that first partitions 3D features into different common-motion clusters and then predicts the motion of each cluster with Kalman filters. The 3D features are computed from a sequence of stereo images by combining two 2D temporal matching modules and one stereo correspondence module. To partition the 3D features into different common-motion clusters, we propose a RANSAC-based clustering method by using rigid body consensus which assumes that all the extracted 3D features on a rigid body have the same 3D motion. By using the motion estimates obtained with the RANSAC-based method as the measurements, we are able to use linear Kalman filters to predict the motion of each cluster, and then, to predict the next position of each 3D feature. Preliminary experiments showed that the proposed 3D predictive visual tracker can serve as a robust 3D feature tracker for an active stereo vision system.
原文英語
主出版物標題Image Analysis Applications and Computer Graphics - 3rd International Computer Science Conference ICSC 1995, Proceedings
編輯Roland T. Chin, Ting-Chuen Pong, Avi C. Naiman, Horace H.S. Ip
發行者Springer Verlag
頁面25-32
頁數8
ISBN(列印)9783540606970
DOIs
出版狀態已發佈 - 1995
事件3rd International Computer Science Conference, ICSC 1995 - Hong Kong, 香港
持續時間: 12月 11 199512月 13 1995

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
1024
ISSN(列印)0302-9743
ISSN(電子)1611-3349

會議

會議3rd International Computer Science Conference, ICSC 1995
國家/地區香港
城市Hong Kong
期間12/11/9512/13/95

ASJC Scopus subject areas

  • 理論電腦科學
  • 一般電腦科學

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