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A real-time visual object tracking system based on Kalman filter and MB-LBP feature matching

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Abstract

Visual tracking has very important applications in practice. Many proposed visual trackers are not suitable for real-time applications because of their huge computational loads or sensitivities against changing environments such as illumination variation. In this paper, we propose a new tracker which uses modified Multi-scale Block Local Binary Patterns (MB-LBP) like feature to characterize the tracked object. Such feature has low computational load and robustness against illumination variation. An updated appearance model is build based on the modified MB-LBP feature. The model is updated in every frame by replacing the appearance model with the features extracted from the most current detected image patch of target. Moreover, we use the predicted information about the target to constructed a smaller searching area for target in new frame. It greatly reduces computational load for target searching. Numerical experiments show that the drift effect of tracker is greatly avoided and the tracker has very effective and robust performance on various test videos.

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Notes

  1. Compared with the other robust features like SIFT and SURF etc., the computation of LBP has much lower computational complexity.

  2. The item in the bracket is the object to track.

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Acknowledgments

The authors would like to thank the associate editor and the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. This work was supported in part by the National Natural Science Foundation of China under grants 61105121 and 61175114, the Natural Science Foundation of Guangdong under grants S2012020010945, the High Level Talent Project of Guangdong Province 2013KJCX0009, China Postdoctoral Science Foundation 2014M560060.

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Authors and Affiliations

  1. College of Automation Science and Engineering, South China University of Technology, Guangzhou, China

    Zebin Cai, Zhenghui Gu & Zhu Liang Yu

  2. Beijing Transportation Information Center, Beijing, China

    Hao Liu

  3. Beijing Transportation Operation Coordination Center, Beijing, China

    Ke Zhang

Authors
  1. Zebin Cai
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  2. Zhenghui Gu
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  3. Zhu Liang Yu
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  4. Hao Liu
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  5. Ke Zhang
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Correspondence to Zhenghui Gu.

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Cai, Z., Gu, Z., Yu, Z.L. et al. A real-time visual object tracking system based on Kalman filter and MB-LBP feature matching. Multimed Tools Appl 75, 2393–2409 (2016). https://doi.org/10.1007/s11042-014-2411-6

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