In this paper, we model multi-agent events in terms of a temporally varying sequence of sub-events, and propose a novel approach for learning, detecting and representing events in...
In this paper, we proposed a novel real-time abnormal event detection framework that requires a short training period and has a fast processing speed. Our approach is based on phas...
The performance of part-based object detectors generally degrades for highly flexible objects. The limited topological structure of models and pre-specified part shapes are two ...
Abstract. We describe an efficient approach to construct shape models composed of contour parts with partially-supervised learning. The proposed approach can easily transfer parts ...
Image categorization could be treated as an effective solution to enable keyword-based image retrieval. In this paper, we propose a novel image categorization approach by learnin...