Article thumbnail
Location of Repository

Pedestrian Detection and Tracking at Crossroads

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

Abstract

[[abstract]]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.

Topics: Pedestrian detection and tracking;Intelligent transportation system;Pedestrian model;Walking rhythm, [[classification]]42
Publisher: Elsevier
Year: 2011
OAI identifier: oai:ir.lib.ntnu.edu.tw:309250000Q/22273
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://ir.lib.ntnu.edu.tw/ir/h... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.