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Automatic Pedestrian Detection and Tracking for Real-Time Video Surveillance

  • Hee-Deok Yang
  • Bong-Kee Sin
  • Seong-Whan Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2688)

Abstract

This paper presents a method for tracking and identifying pedestrians from video images taken by a fixed camera at an entrance. A pedestrian may be totally or partially occluded in a scene for some period of time. The proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. We compared the proposed method with other related methods using color and shape features, and analyzed the features’ stability. Experimental results with various real video data revealed that real time pedestrian tracking and recognition is possible with increased stability over 5–15% even under occasional occlusions in video surveillance applications.

Keywords

Face Recognition Video Surveillance Appearance Model Pedestrian Detection Intensity Cluster 
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 2003

Authors and Affiliations

  • Hee-Deok Yang
    • 1
  • Bong-Kee Sin
    • 2
  • Seong-Whan Lee
    • 1
  1. 1.Center for Artificial Vision ResearchKorea UniversitySeoulKorea
  2. 2.Department of Computer MultimediaPukyong National UniversityPusanKorea

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