Measuring Object Speed Using Stereo Tracking
Stereo vision provides us the ability to perceive objects in 3D. By continuously tracking an object in stereo videos, the information about object motion can be acquired. In this paper, we propose a novel method which unifies the tracking and speed measuring within the Bayesian filtering framework and solves this problem using particle filtering approach. Vehicle speed measuring is studied as a specific example. Environment constraints are integrated into the tracking for reducing the uncertainty to achieve more robust and accurate results. Experiment results on both synthetic and real traffic sequences demonstrate the accuracy and effectiveness of our proposed method.
Junda Zhu Yuan F. Zheng Robert E. Ewing
Department of Electrical and Computer Engineering The Ohio State University 2015 Neil Avenue,Columbu Air Force Research Laboratory Wright Patterson AFB,Ohio 45433
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
5949-5954
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）