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Object tracking by color distribution fields with adaptive hierarchical structure

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Abstract

The essence of visual tracking is to distinguish the target from background, so how to describe the difference between target and background is a key problem. In this paper, tracking algorithm by color distribution fields with adaptive hierarchical structure is presented to solve this problem. First, multichannel color distribution fields are presented for appearance modeling, which represents color distinction between the target and background. Second, in order to adapt to the individuality of each target, the hierarchical structure of its color distribution fields are generated via k-means cluster. Third, weighted multichannel \(L_1 \) distance is used to measure the similarity between the candidate region and the template; the weight of each channel is adjusted online according to its discrimination. Finally, a search strategy based on simulated annealing is proposed to improve the search efficiency and reduce the probability of falling into the local optimum. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art tracking algorithms.

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Acknowledgments

This work was supported by the National Nature Science Foundation of China (Nos. 61379151, 61521003), the Henan Province Science Found for Distinguished Young Scholars of China (No. 14410051-0001), the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (No. 2014B-AH30B01).

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Authors and Affiliations

  1. National Digital Switching System Engineering and Technological R&D Center, Zhengzhou, China

    Yawen Wang, Hongchang Chen, Shaomei Li, Jianpeng Zhang & Chao Gao

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  1. Yawen Wang
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  2. Hongchang Chen
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  3. Shaomei Li
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  4. Jianpeng Zhang
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  5. Chao Gao
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Correspondence to Yawen Wang.

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Wang, Y., Chen, H., Li, S. et al. Object tracking by color distribution fields with adaptive hierarchical structure. Vis Comput 33, 235–247 (2017). https://doi.org/10.1007/s00371-015-1189-5

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