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A Real-Time Active Pedestrian Tracking System Inspired by the Human Visual System

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Abstract

Pedestrian detection and tracking play a significant role in surveillance. Despite the numerous detection and tracking methods proposed in the literature, when the pedestrian is too small to recognize, which is a common case in modern surveillance systems, all methods fail. In order to deal with such case, we propose an active pedestrian tracking system inspired by the human visual system. A coarse-to-fine pedestrian detection algorithm is proposed for the small pedestrian detection by combining the Gaussian mixture model background subtraction with the histogram of oriented gradient detection. In addition, a three-dimensional pan–tilt–zoom control model is presented, which requires no calibration and is more accurate than other control models. In order to actively track a pedestrian in real time, we utilize an active control algorithm and a tracking–learning–detection tracker. Experimental results demonstrate that our active tracking system is both efficient and effective.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (Nos. 61175096, 61173079, 61472163 and 61472163), Specialized Fund for Joint Building Program of Beijing municipal Education Commission, and the Key Project of Natural Science Foundation of Shandong Province (No. ZR2011FZ003). The authors would like to thank the editors and the anonymous reviewers for their constructive comments and suggestions.

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Authors and Affiliations

  1. Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing, 100081, People’s Republic of China

    Yuxia Wang, Qingjie Zhao, Bo Wang, Yu Zhang & Wei Guo

  2. Provincial Key Laboratory for Network Based Intelligent Computing, University of Jinan, Jinan, 250022, People’s Republic of China

    Qingjie Zhao, Shixian Wang & Zhiquan Feng

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  1. Yuxia Wang
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  2. Qingjie Zhao
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  3. Bo Wang
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  4. Shixian Wang
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  5. Yu Zhang
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  6. Wei Guo
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  7. Zhiquan Feng
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Correspondence to Qingjie Zhao.

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Wang, Y., Zhao, Q., Wang, B. et al. A Real-Time Active Pedestrian Tracking System Inspired by the Human Visual System. Cogn Comput 8, 39–51 (2016). https://doi.org/10.1007/s12559-015-9334-z

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