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.
['Simon Denman', 'Vinod Chandran', 'Sridha Sridharan', 'Clinton Fookes']
A Multi-Class Tracker Using a Scalable Condensation Filter