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

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/51633

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51633

Title:	Integrated video object tracking with applications in trajectory-based event detection
Authors:	Cheng,HY;Hwang,JN
Contributors:	資訊工程學系
Keywords:	PROBABILISTIC DATA ASSOCIATION;PARTICLE FILTERS;SURVEILLANCE;RECOGNITION;MODELS;APPEARANCE;ALGORITHMS;TUTORIAL;MOTION
Date:	2011
Issue Date:	2012-03-27 18:58:02 (UTC+8)
Publisher:	國立中央大學
Abstract:	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.
Relation:	JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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