Abstract. A new theoretical framework for the analysis of linear combiners is presented in this paper. This framework extends the scope of previous analytical models, and provides ...
We present a new Bayesian approach to object identification: variants. By object identification we mean the detection of the member (regular variant) of a given statistical popula...
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothe...
Outdoor scene classification is challenging due to irregular geometry, uncontrolled illumination, and noisy reflectance distributions. This paper discusses a Bayesian approach to ...
Yanghai Tsin, Robert T. Collins, Visvanathan Rames...
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...