NDLI: A distributed architecture for collaborative real-time video tracking

Content Provider	IEEE Xplore Digital Library
Author	Wei Qu Schonfeld, D. Mohamed, M.A.
Copyright Year	2007
Description	Author affiliation: Motorola Labs, Schaumburg (Wei Qu)
Abstract	Most existing multiple object tracking techniques suffer from the well-known "multi-object occlusion" problem and/or immense computational cost due to the use of high- dimensional joint state representation. In this paper, we present a novel distributed Bayesian framework using multiple collaborative cameras for robust and efficient multiple object tracking with significant and persistent occlusion. When the objects are in close proximity or present multi-object occlusions in a particular camera view, camera collaboration between different views is activated in order to handle the multi-object occlusion problem. Moreover, we propose to model the camera collaboration likelihood density by using epipolar geometry with particle filter implementation. The performance of our approach has been demonstrated on real-world video data.
Starting Page	2102
Ending Page	2107
File Size	250116
Page Count	6
File Format	PDF
ISBN	9781424409907
DOI	10.1109/ICSMC.2007.4413581
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Collaboration Cameras Robustness Particle filters Computational efficiency Bayesian methods Computer architecture Solid modeling Geometry Video surveillance
Content Type	Text
Resource Type	Article

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