Abstract
Color and texture provide important visual information for real-time tracking of non-rigid and partially occluded objects. Recent developments have shown the robustness and effectiveness of color based tracking algorithms, especially for tracking tasks where object shape exhibits dramatic variability. In this article we solve the problem by tracking color distributions of background and foreground (object) points simultaneously. The key feature of our approach is careful selection of histogram resolution (or kernel radius) on each frame of a sequence.
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Akhriev, A. (2007). Object Tracking Via Uncertainty Minimization. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_58
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DOI: https://doi.org/10.1007/978-3-540-76856-2_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76855-5
Online ISBN: 978-3-540-76856-2
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