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In this paper, a new collaborative tracking algorithm is put forward to track multiple objects in video streams. First, we suggest a robust color-based tracker whose model is updated by online learned contextual information. A recursive method is performed to improve the estimation accuracy and the robustness to cluttered environment. Then, we extend this tracker to multiple targets. To avoid the...
This paper addresses the problems of tracking targets which undergo rapid and significant appearance changes. Our starting point is a successful, state-of-the-art tracker based on an adaptive coupled-layer visual model [10]. In this paper, we identify four important cases when the original tracker often fails: significant scale changes, environment clutter, and failures due to occlusion and rapid...
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