Discriminative Multiple Target Tracking

In this chapter, we introduce a metric learning framework to learn a single discriminative appearance model for robust visual tracking of multiple targets. The single appearance model effectively captures the discriminative visual information among the different visual targets as well as the background. The appearance modeling and the tracking of the multiple targets are all cast in a discriminative metric learning framework. We manifest that an implicit exclusive principle is naturally reinforced in the proposed framework, which renders the tracker to be robust to cross occlusions among the multiple targets. We demonstrate the efficacy of the proposed multiple target tracker on benchmark visual tracking sequences, and real-world video sequences as well.