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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2012  >  12(5): 110-118
CHENG Ru-zhong, ZHAO Yong, WANG Zhi-zhong, XU Jia-yao, WANG Xin-an. Real-time pedestrian detecting and warning system[J]. Journal of Traffic and Transportation Engineering, 2012, 12(5): 110-118. doi: 10.19818/j.cnki.1671-1637.2012.05.015
Citation: CHENG Ru-zhong, ZHAO Yong, WANG Zhi-zhong, XU Jia-yao, WANG Xin-an. Real-time pedestrian detecting and warning system[J]. Journal of Traffic and Transportation Engineering, 2012, 12(5): 110-118. doi: 10.19818/j.cnki.1671-1637.2012.05.015
shu

Real-time pedestrian detecting and warning system

doi: 10.19818/j.cnki.1671-1637.2012.05.015
  • 1.

    School of Shenzhen Graduate, Peking University, Shenzhen 518055, Guangdong, China

  • 2.

    Hong Kong Productivity Council, Hong Kong, China

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    Abstract
  • A real-time pedestrian detecting and warning system(PDWS) based on the features of pedestrian side was proposed to solve the problem of pedestrian protection in serious traffic accidents. The system consisted of two parts, detecting module and warning module. The feature extraction and detection pedestrian were completed by using side pedestrian sample dataset in detecting module, Haar and HOG features together with AdaBoost and SVM classifiers were applied to complete the feature extraction and detection. Window-dividing method and operator context scanning(OCS) method were used to improve the detecting efficiency, and a result with both high detection rate and low false alarm rate was obtained. The velocity and angular velocity of automobile together with the distance of detected pedestrian were merged in warning module, so the system could judge the collision risk for the pedestrian in the front. The system and the algorithms were tested toward the pedestrian crossing street with a complex urban envirnment in real vehicle. Test result shows that for the images with 704 Pixel×576 Pixel, the frame rate is about 13-18 frame·s-1, the detecting rate is above 85%, the false detecting rate is below 1%, and the warning response time is less than 1 s. The result meets the requirements of on-board active safety system both in accuracy and real-time use.

     

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