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Face Tracking Algorithm Based on Mean Shift and Ellipse Fitting

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Neural Information Processing (ICONIP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4233))

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Abstract

The mean shift algorithm is an efficient technique for object tracking. However, it has a shortcoming that it can’t adjust scale with object during tracking process. There are presently no effective ways to solve this problem. The kernel bandwidth of mean shift tracker in one frame is generally steered by the object scale obtained in the previous frame, so it is very important for mean shift tracker to correctly describe the scale of the target in very frame. In accordance with the kernel-bandwidth effect on the mean shift tracker and the property of face, this paper introduces a new idea that uses direct least square ellipse fitting to adjust the facial scale. The experimental results demonstrate the efficiency of this algorithm. Its performance has been proven superior to the original mean shift tracking algorithm.

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Author information

Authors and Affiliations

  1. Department of Radio Engineering, Southeast University, 210096, Nanjing, China

    Jianpo Gao, Zhenyang Wu & Yujian Wang

Authors
  1. Jianpo Gao
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  2. Zhenyang Wu
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  3. Yujian Wang
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, The Chinese Univ. of Hong Kong, Shatin, N.T., Hong Kong

    Irwin King

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  3. The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Lai-Wan Chan

  4. Department of Computer Science and Engineering & Center for Cognitive Science, The Ohio State University, OH 43210, Columbus

    DeLiang Wang

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© 2006 Springer-Verlag Berlin Heidelberg

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Gao, J., Wu, Z., Wang, Y. (2006). Face Tracking Algorithm Based on Mean Shift and Ellipse Fitting. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893257_30

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  • DOI: https://doi.org/10.1007/11893257_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46481-5

  • Online ISBN: 978-3-540-46482-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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