Passenger Flow Detection of Video Surveillance: A Case Study of High-Speed Railway Transport Hub in China

  • Xie Zhengyu Beijing Jiaotong University
  • Jia Limin Beijing Jiaotong University
  • Wang Li Beijing Jiaotong University
Keywords: Image analysis, image recognition, background model, passenger flow status, high-speed railway transport hub.

Abstract

Detect moving object from a video sequence is a fundamental and critical task in many computer vision applications. With video surveillance system of high-speed railway transport hub, one of the aims for passenger flow detection is to accurately and promptly detect potential safety hazard hidden in passenger flow. In this paper, a procedure of passenger flow detection in high-speed railway transport hub is presented. According to the key steps of procedure, a modified background model based on Dempster-Shafer theory, and a passenger flow status recognition algorithm based on features of image connected domain are proposed to improve the accuracy and real-time performance of passenger flow detection. Credit and effects of proposed methods were proved by experiment on data from high-speed railway transport hub video surveillance system.

DOI: http://dx.doi.org/10.5755/j01.eee.21.1.9805

Published
2015-02-09
How to Cite
Zhengyu, X., Limin, J., & Li, W. (2015). Passenger Flow Detection of Video Surveillance: A Case Study of High-Speed Railway Transport Hub in China. Elektronika Ir Elektrotechnika, 21(1), 48-53. https://doi.org/10.5755/j01.eee.21.1.9805
Section
SYSTEM ENGINEERING, COMPUTER TECHNOLOGY