A Robust Tracking Algorithm in Crowded Environment
Reliable tracking of multiple people in cluttered or complex situations is a challenging visual surveillance problem since the high density of objects results in occlusion. In order to deal with this problem, multiple synchronized cameras were mounted at various heights in our experiment. To ensure the existence of the homography, it is necessary to assume that different views share a common dominant ground plane. Thus, corresponding people have to be located within the multi-camera surveillance system, accurate multi-people localizing is an important prerequisite to reliable tracking. In this paper, we present a novel approach to fusing foreground information on planes of different height from multiple views to increase accurateness of localization. Our method does not require fully camera calibration. First we obtain the foreground likelihood maps in each view by modeling the background using codebook algorithm. Then we compute homographies induced by multiple planes and obtain the localization of multiple people at multiple planes. Finally, we adopt an algorithm of featurebased using Kalman filter motion to handle multiple objects tracking at multiple plane. The experimental results show that our method is valid and has nice robustness to the occlusion in crowed environments.
Localizing homography multiple planes multi-camera
Mingxin Jiang Hongyu Wang
College of Electrical&lnformation Engineering Dalian University of Technology, Dalian, China College College of Electrical&lnformation Engineering Dalian University of Technology, Dalian, China
国际会议
2011 International Conference on Mechatronics and Applied Mechanics(2011年机电一体化与应用力学国际会议 ICMAM 2011)
香港
英文
1336-1339
2011-12-27（万方平台首次上网日期，不代表论文的发表时间）