We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and po...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
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 method for efficiently generating a representation of a multi-modal posterior probability distribution. The technique combines ideas from RANSAC and particle filterin...
We present a novel framework for multiple object tracking in which the problems of object detection and data association are expressed by a single objective function. The framewor...
Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit ...