Coordination of Multiple Agents for Probabilistic Object Tracking
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
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ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Multicamera People Tracking with a Probabilistic Occupancy Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
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GCIS '09 Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01
Multi-Camera Networks: Principles and Applications
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Human Tracking Using Spatialized Multi-level Histogram and Mean Shift
CRV '10 Proceedings of the 2010 Canadian Conference on Computer and Robot Vision
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This paper presents a multi-camera surveillance system for motion detection and object tracking based on Motion History Image (MHI), Color-based Particle Filtering (CPF), and a novel relay strategy. The system is composed of two Pan-Tilt-Zoom (PTZ) cameras completely calibrated and placed on desks. Initially, both cameras work as stationary Scene View Camera (SVC) to detect objects for abnormal human motion events such as sudden falling using MHI. If an object is detected in one camera, the other camera can then be controlled to work as Object View Camera (OVC), follow this object, and get zoom-in images using CPF. The states of the tracked object can be exchanged across cameras so that in case that the OVC loses the object, the SVC has sufficient knowledge of the object location, and it can become a new OVC to run the tracking relay. Meanwhile, the original OVC should be reset to work as SVC in order not to lose the global view. Two scenarios, in which the cameras have large or little overlapping field of view, are proposed and analyzed. Experimental study further demonstrates the effectiveness of the proposed system.