Sample and Pixel Weighting Strategies for Robust Incremental Visual Tracking

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serval:BIB_E81DF34003A9
Type
Article: article from journal or magazin.
Collection
Publications
Title
Sample and Pixel Weighting Strategies for Robust Incremental Visual Tracking
Journal
IEEE Transactions on Circuits and Systems for Video Technology
Author(s)
Cruz-Mota J., Bierlaire M., Thiran J.P.
ISSN
1051-8215
Publication state
Published
Issued date
2013
Volume
23
Number
5
Pages
898-911
Language
english
Abstract
In this paper, we introduce the incremental temporally weighted principal component analysis (ITWPCA) algorithm, based on singular value decomposition update, and the incremental temporally weighted visual tracking with spatial penalty (ITWVTSP) algorithm for robust visual tracking. ITWVTSP uses ITWPCA for computing incrementally a robust low dimensional subspace representation (model) of the tracked object. The robustness is based on the capacity of weighting the contribution of each single sample to the subspace generation to reduce the impact of bad quality samples, reducing the risk of model drift. Furthermore, ITWVTSP can exploit the a priori knowledge about important regions of a tracked object. This is done by penalizing the tracking error on some predefined regions of the tracked object, which increases the accuracy of tracking. Several tests are performed on several challenging video sequences, showing the robustness and accuracy of the proposed algorithm, as well as its superiority with respect to state-of-the-art techniques.
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06/01/2014 17:54
Last modification date
20/08/2019 16:10
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