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Fragment-based real-time object tracking: a sparse representation approach

Kumar, Naresh MS and Parate, Priti and Babu, Venkatesh R (2012) Fragment-based real-time object tracking: a sparse representation approach. In: 2012 19th IEEE International Conference on Image Processing (ICIP), Sept. 30 2012-Oct. 3 2012, Orlando, FL, pp. 433-436.

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Official URL: http://dx.doi.org/10.1109/ICIP.2012.6466889


Real-time object tracking is a critical task in many computer vision applications. Achieving rapid and robust tracking while handling changes in object pose and size, varying illumination and partial occlusion, is a challenging task given the limited amount of computational resources. In this paper we propose a real-time object tracker in l(1) framework addressing these issues. In the proposed approach, dictionaries containing templates of overlapping object fragments are created. The candidate fragments are sparsely represented in the dictionary fragment space by solving the l(1) regularized least squares problem. The non zero coefficients indicate the relative motion between the target and candidate fragments along with a fidelity measure. The final object motion is obtained by fusing the reliable motion information. The dictionary is updated based on the object likelihood map. The proposed tracking algorithm is tested on various challenging videos and found to outperform earlier approach.

Item Type: Conference Paper
Series.: IEEE International Conference on Image Processing ICIP
Publisher: IEEE
Additional Information: Copyright of this article belongs to IEEE.
Keywords: Object Tracking; Fragment Tracking; Motion Estimation; l(1) Minimization; Sparse Representation
Department/Centre: Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited: 23 Sep 2013 08:26
Last Modified: 23 Sep 2013 08:26
URI: http://eprints.iisc.ac.in/id/eprint/47280

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