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Particle Filter Based Tracking of Moving Object from Image Sequence

  • Yuji Iwahori
  • Toshihiro Takai
  • Haruki Kawanaka
  • Hidenori Itoh
  • Yoshinori Adachi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)

Abstract

Object tracking is an important topic in computer vision and image recognition. The probabilistic approach using the particle filter has been recently used for the tracking of moving objects. Based on our trajectory recording system of the soccer scene with multiple video cameras at one view point, we propose the extended approach to increase the tracking robustness and accuracy using the particle filter. The proposed approach makes it possible to pass the necessary particle information using the color histogram and other key factors from one image to the next image, which are taken through the different camera scene with one PC. The performance of the proposed approach is evaluated in the experiments with real video sequence. It is shown that one PC can handle two video images in real-time.

Keywords

Particle Filter Tracking Target Target Size Color Histogram Motion Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yuji Iwahori
    • 1
  • Toshihiro Takai
    • 2
  • Haruki Kawanaka
    • 3
  • Hidenori Itoh
    • 2
  • Yoshinori Adachi
    • 1
  1. 1.Chubu UniversityKasugaiJapan
  2. 2.Nagoya Institute of TechnologyNagoyaJapan
  3. 3.Aichi Prefectural UniversityJapan

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