In this paper, we present a novel decentralized Bayesian framework using multiple collaborative cameras for robust and efficient multiple object tracking with significant and pe...
We present a novel multi-object tracking algorithm based on multiple hypotheses about the trajectories of the objects. Our work is inspired by Reid's multiple hypothesis trac...
In this paper we show that Ullman and Basri’s linear combination (LC) representation, which was originally proposed for alignment-based object recognition, can be used for outli...
This paper presents the fundamental theory and algorithms for identifying the most preferred alternative for a decision maker (DM) having a non-centrist (or extremist) preferentia...
Reliable tracking of multiple moving objects in video is an interesting challenge, made difficult in real-world video by various sources of noise and uncertainty. We propose a Bay...