Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System

  • Lie Guo Dalian University of Technology
  • Mingheng Zhang Dalian University of Technology, School of Automotive Engineering No.2 Linggong Road, Ganjingzi District, Dalian 116024, China
  • Linhui Li Dalian University of Technology, School of Automotive Engineering No.2 Linggong Road, Ganjingzi District, Dalian 116024, China
  • Yibing Zhao Dalian University of Technology, School of Automotive Engineering No.2 Linggong Road, Ganjingzi District, Dalian 116024, China
  • Yingzi Lin Department of Mechanical and Industrial Engineering, College of Engineering, Northeastern University 360 Huntington Avenue, Boston, MA 02115, USA
Keywords: automobile safety, pedestrian protection, gentle AdaBoost, template matching,

Abstract

A novel pedestrian detection system based on vision in urban traffic situations is presented to help the driver perceive the pedestrian ahead of the vehicle. To enhance the accuracy and to decrease the time spent on pedestrian detection in such complicated situations, the pedestrian is detected by dividing their body into several parts according to their corresponding features in the image. The candidate pedestrian leg is segmented based on the gentle AdaBoost algorithm by training the optimized histogram of gradient features. The candidate pedestrian head is located by matching the pedestrian head and shoulder model above the region of the candidate leg. Then the candidate leg, head and shoulder are combined by parts constraint and threshold adjustment to verify the existence of the pedestrian. Finally, the experiments in real urban traffic circumstances were conducted. The results show that the proposed pedestrian detection method can achieve pedestrian detection rate of 92.1% with the average detection time of 0.2257 s.

Author Biographies

Lie Guo, Dalian University of Technology
School of Automotive Engineering
Mingheng Zhang, Dalian University of Technology, School of Automotive Engineering No.2 Linggong Road, Ganjingzi District, Dalian 116024, China
Ph.D.
Linhui Li, Dalian University of Technology, School of Automotive Engineering No.2 Linggong Road, Ganjingzi District, Dalian 116024, China
Associate Professor, Ph.D.
Yibing Zhao, Dalian University of Technology, School of Automotive Engineering No.2 Linggong Road, Ganjingzi District, Dalian 116024, China
Ph.D.
Yingzi Lin, Department of Mechanical and Industrial Engineering, College of Engineering, Northeastern University 360 Huntington Avenue, Boston, MA 02115, USA
Associate Professor, Ph.D.

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Published
2016-04-25
How to Cite
1.
Guo L, Zhang M, Li L, Zhao Y, Lin Y. Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System. PROMET [Internet]. 2016Apr.25 [cited 2020Feb.26];28(2):133-42. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/1720
Section
Articles