We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
Traditional aspect graphs are topology-based and are impractical for articulated objects. In this work we learn a small number of aspects, or prototypical views, from video data. ...
The use of video sequences for face recognition has been relatively less studied than image-based approaches. In this paper, we present a framework for face recognition from video...
We address the problem of estimating human pose in video sequences, where rough location has been determined. We exploit both appearance and motion information by defining suitabl...
This paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackers' motion...