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2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06)
A Multi-Class Tracker Using a Scalable Condensation Filter
Sydney, NSW, Australia
November 22-November 24
ISBN: 0-7695-2688-8
Simon Denman, Queensland University of Technology, Australia
Vinod Chandran, Queensland University of Technology, Australia
Sridha Sridharan, Queensland University of Technology, Australia
Clinton Fookes, Queensland University of Technology, Australia
Tracking systems are typically targeted towards tracking a single class of object. In many real world situations, and in the ETISEO evaluation, it is advantageous to be able to track multiple classes of objects. In this paper we describe the adaptation of a single class tracking system to a multi-class tracking system, and describe a modified version of the condensation filter that can be used to track all objects, of all classes. We show that by using simple targeted detectors, we can achieve accurate tracking and can accurately distinguish between classes.
Citation:
Simon Denman, Vinod Chandran, Sridha Sridharan, Clinton Fookes, "A Multi-Class Tracker Using a Scalable Condensation Filter," avss, pp.25, 2006 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS'06), 2006
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