A new algorithm is presented for the automatic segmentation and classification of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classification and ta...
Zhao Yi, Antonio Criminisi, Jamie Shotton, Andr...
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
We consider the problem of monocular 3d body pose tracking from video sequences. This task is inherently ambiguous. We propose to learn a generative model of the relationship of bo...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...
In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to learn the collective behavior patterns of pedestrians in crowded scenes. Collective behaviors ...
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...