In this paper, we introduce a first-order probabilistic model that combines multiple cues to classify human activities from video data accurately and robustly. Our system works in...
We augment the I/O automaton model of Lynch and Tuttle with probability, as a step toward the ultimate goal of obtaining a useful tool for specifying and reasoning about asynchron...
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
Probabilistic Latent Semantic Analysis (PLSA) has become a popular topic model for image clustering. However, the traditional PLSA method considers each image (document) independen...
We present new results on the relation between context-free parsing strategies and their probabilistic counter-parts. We provide a necessary condition and a sufficient condition f...