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ICMCS
2007
IEEE

Robust People Detection and Tracking in a Multi-Camera Indoor Visual Surveillance System

14 years 6 months ago
Robust People Detection and Tracking in a Multi-Camera Indoor Visual Surveillance System
In this paper we describe the analysis component of an indoor, real-time, multi-camera surveillance system. The analysis includes: (1) a novel feature-level foreground segmentation method which achieves efficient and reliable segmentation results even under complex conditions, (2) an efficient greedy search based approach for tracking multiple people through occlusion, and (3) a method for multicamera handoff that associates individual trajectories in adjacent cameras. The analysis is used for an 18 camera surveillance system that has been running continuously in an indoor business over the past several months. Our experiments demonstrate that the processing method for people detection and tracking across multiple cameras is fast and robust.
Tao Yang, Francine Chen, Don Kimber, Jim Vaughan
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICMCS
Authors Tao Yang, Francine Chen, Don Kimber, Jim Vaughan
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