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Pedestrian Recognition in Far-Infrared Images by Combining Boosting-Based Detection and Skeleton-Based Stochastic Tracking

  • Ryusuke Miyamoto
  • Hiroki Sugano
  • Hiroaki Saito
  • Hiroshi Tsutsui
  • Hiroyuki Ochi
  • Ken’ichi Hatanaka
  • Yukihiro Nakamura
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)

Abstract

Nowadays, pedestrian recognition in far-infrared images toward realizing a night vision system becomes a hot topic. However, sufficient performance could not be achieved by conventional schemes for pedestrian recognition in far-infrared images. Since the properties of far-infrared images are different from visible images, it is not known what kind of scheme is suitable for pedestrian recognition in far-infrared images. In this paper, a novel pedestrian recognition scheme combining boosting-based detection and skeleton-based stochastic tracking suitable for recognition in far-infrared images is proposed. Experimental results by using far-infrared sequences show the proposed scheme achieves highly accurate pedestrian recognition by combining accurate detection with few false positives and accurate tracking.

Keywords

Pedestrian Detection Accurate Tracking Skeleton Model Mersenne Twister Pedestrian 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

  • Ryusuke Miyamoto
    • 1
    • 2
  • Hiroki Sugano
    • 1
    • 2
  • Hiroaki Saito
    • 3
  • Hiroshi Tsutsui
    • 1
  • Hiroyuki Ochi
    • 1
    • 2
  • Ken’ichi Hatanaka
    • 3
  • Yukihiro Nakamura
    • 1
    • 2
  1. 1.Dept. of Communications and Computer EngineeringKyoto UniversityKyotoJapan
  2. 2.Kyoto Center, Synthesis CorporationKyotoJapan
  3. 3.Sumitomo Electric Industries, Ltd.OsakaJapan

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