Robust Tracking Based on Boosted Color Soft Segmentation and ICA-R

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Authors Fan Yang, Huchuan Lu, Yen-Wei Chen
Journal/Conference Name IEEE International Conference on Image Processing
Paper Category
Paper Abstract In this paper, we propose a novel approach for robust visual tracking. To separate the foreground from the background, we propose a novel Boosted Color Soft Segmentation (BCSS) algorithm and incorporate Independent Component Analysis with Reference (ICA-R) into the tracking framework. In addition, we design a scheme to fuse and update BCSS and ICA-R. We also propose adaptive scale of tracking window to handle objects' scale changes. Experiments shows that our approach is more robust than some popular tracking systems.
Date of publication 2010
Code Programming Language MATLAB

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