Integrated video object tracking with applications in trajectory-based event detection

被引:35
|
作者
Cheng, Hsu-Yung [1 ]
Hwang, Jenq-Neng [2 ]
机构
[1] Natl Cent Univ, Dept Comp Sci & Informat Engn, Jhongli 32001, Taoyuan County, Taiwan
[2] Univ Washington, Dept Elect Engn, Paul Allen Ctr, Seattle, WA 98195 USA
关键词
Tracking; Kalman Filter; Adaptive particle sampling; Data Association; Trajectory analysis; Event detection; Intelligent Surveillance; Video Analysis; PARTICLE FILTERS; SURVEILLANCE; RECOGNITION; APPEARANCE; ALGORITHMS; TUTORIAL; MOTION; MODELS;
D O I
10.1016/j.jvcir.2011.07.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This work presents an automated and integrated framework that robustly tracks multiple targets for video-based event detection applications. Integrating the advantages of adaptive particle sampling and mathematical tractability of Kalman filtering, the proposed tracking system achieves both high tracking accuracy and computational simplicity. Occlusion and segmentation error cases are analyzed and resolved by constructing measurement candidates via adaptive particle sampling and an enhanced version of probabilistic data association. Also, we integrate the initial occlusion handling module in the tracking system to backtrack and correct the object trajectories. The reliable tracking results can serve as the foundation for automatic event detection. We also demonstrate event detection by classifying the trajectories of the tracked objects from both traffic monitoring and human surveillance applications. The experimental results have shown that the proposed tracking mechanism can solve the occlusion and segmentation error problems effectively and the events can be detected with high accuracy. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:673 / 685
页数:13
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