Independently Moving Object Detection and Tracking using Stereo Vision
We present an approach for detecting and tracking independently moving objects from a mobile platform using uncalibrated stereo cameras. Firstly, scale invariant feature transform (SIFT) features are detected and a novel multiview matching method is proposed for simultaneous stereo matching and motion tracking of the detected features. A multiview geometric constraint, derived from the relative camera positions in pairs of consecutive stereo views, is then derived for independent motion detection. Finally, a dimensional variable particle filter is introduced for joint detection and tracking of multiple independently moving objects. Experimental results on real-world stereo sequences demonstrate the effectiveness and robustness of our method.
moving object detection stereo vision feature matching particle filter
Hao Sun Naser El-Sheimy Cheng Wang Boliang Wang
School of Electrical Science and Engineering National University of Defense TechnologyChangsha,Hunan Department of Geomatics Engineering University of Calgary Calgary,Alberta,Canada Department of Computer Science Xiamen University Xiamen,Fujian Province,China
国际会议
2010 IEEE信息与自动化国际会议(ICIA 2010)
哈尔滨
英文
1-6
2010-06-20（万方平台首次上网日期，不代表论文的发表时间）