Object recognition systems aiming to work in real world settings should use multiple cues in order to achieve robustness. We present a new cue integration scheme which extends the...
Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
In this paper, we propose a data-driven approach that extracts prior information for segmentation of the left ventricle in cardiac MR images of transplanted rat hearts. In our app...
Xiao Jia, Chao Li, Ying Sun, Ashraf A. Kassim, Yij...
We present an emotion recognition system based on a probabilistic approach to adaptive processing of Facial Emotion Tree Structures (FETS). FETS are made up of localized Gabor fea...
We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...