This paper presents a novel approach for tracking humans and objects under severe occlusion. We introduce a new paradigm for multiple hypotheses tracking, observe-and-explain, as ...
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
One of the key problems in computer vision and pattern recognition is tracking. Multiple objects, occlusion, and tracking moving objects using a moving camera are some of the chal...
In kernel-based video object tracking, the use of single kernel often suffers from the occlusion. In order to provide more robust tracking performance, multiple inter-related kern...
Most methods for multiple camera tracking rely on accurate calibration to associate data from multiple cameras. However, it often is not easy to have an accurate calibration in so...
Nam Trung Pham, Richard Chang, Karianto Leman, Tec...