Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Abstract. Foreground and background segmentation is a typical problem in computer vision and medical imaging. In this paper, we propose a new learning based approach for 3D segment...
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Abstract—A probabilistic analytical framework for decentralized load balancing (LB) strategies for heterogeneous distributed-computing systems (DCSs) is presented with the overal...
This paper proposes a probabilistic search algorithm to boost the computational efficiency of face detection in video sequences. The algorithm sequentially predicts the probabili...
Atsushi Matsui, Simon Clippingdale, Takashi Matsum...