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Short-Term Memory-Based Object Tracking

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Image Analysis and Recognition (ICIAR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3212))

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Abstract

In this paper, we propose a new tracking method that adapts itself to suddenly changing appearance. The proposed method is based on color-based particle filtering. A short-term memory model is introduced to handle the cases of sudden appearance changes, occlusion, disappearance and reappearance of tracked objects. A new target model update method is implemented. Our method is robust and versatile for a modest computational cost. Desirable tracking results are obtained.

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Author information

Authors and Affiliations

  1. Dept. of Computer Engineering, The Catholic University of Korea, #43-1 Yokkok 2-dong Wonmi-Gu, Puchon City Kyonggi-Do, Korea

    Hang-Bong Kang & Sang-Hyun Cho

Authors
  1. Hang-Bong Kang
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  2. Sang-Hyun Cho
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Editor information

Editors and Affiliations

  1. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed Kamel

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© 2004 Springer-Verlag Berlin Heidelberg

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Kang, HB., Cho, SH. (2004). Short-Term Memory-Based Object Tracking. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_73

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  • DOI: https://doi.org/10.1007/978-3-540-30126-4_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23240-7

  • Online ISBN: 978-3-540-30126-4

  • eBook Packages: Springer Book Archive

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