We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Abstract In a line of recent development, probabilistic constructions of universal, homogeneous objects have been provided in various categories of ordered structures, such as caus...
We present a practical framework for detecting and modeling 3D static occlusions for wide-baseline, multi-camera scenarios where the number of cameras is small. The framework cons...
This paper describes a probabilistic syntactic approach to the detection and recognition of temporally extended activities and interactions between multiple agents. A complete sys...
We present a novel approach for non-stationarity detection in natural images by exploiting the prior knowledge of the independent component structure of scene statistics. Our prop...