Pedestrian detection and tracking at crossroads

Chia Jung Pai, Hsiao Rong Tyan, Yu Ming Liang, Hong Yuan Mark Liao*, Sei Wang Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

86 Citations (Scopus)


This paper presents a system that can perform pedestrian detection and tracking using vision-based techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method, which combines the use of a pedestrian model as well as the walking rhythm of pedestrians to detect and track walking pedestrians. Through integrating some spatial and temporal information grabbed by a vision system, we are able to develop a reliable system that can be used to prevent traffic accidents happened at crossroads. In addition, the proposed system can deal with the occlusion problem. Experimental results obtained by executing some real world cases have demonstrated that the proposed system is indeed superb.

Original languageEnglish
Pages (from-to)1025-1034
Number of pages10
JournalPattern Recognition
Issue number5
Publication statusPublished - 2004 May


  • Intelligent transportation system
  • Pedestrian detection and tracking
  • Pedestrian model
  • Walking rhythm

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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