GUO Ai-ying, XU Mei-hua, RAN Feng, WANG Qi. Model of real-time pedestrian detection under vehicle environment based on CS-SD[J]. Journal of Traffic and Transportation Engineering, 2016, 16(6): 132-139.
Citation: GUO Ai-ying, XU Mei-hua, RAN Feng, WANG Qi. Model of real-time pedestrian detection under vehicle environment based on CS-SD[J]. Journal of Traffic and Transportation Engineering, 2016, 16(6): 132-139.

Model of real-time pedestrian detection under vehicle environment based on CS-SD

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  • Author Bio:

    GUO Ai-ying(1984-), female, lecturer, doctoral student, +86-21-56331632, gayshh@shu.edu.cn

    XU Mei-hua(1957-), female, professor, PhD, +86-21-56331632, mhxu@shu.edu.cn

  • Received Date: 2016-05-21
  • Publish Date: 2016-12-25
  • In order to solve the real-time problem in the advanced driver assistant system, a model of pedestrian detection based on the calibration of side-of-pavement line and saliency texture detection (CS-SD) and the location histogram of oriented gradient (L-HOG) was proposed.The CS-SD algorithm was used instead of exhaustive search to quickly mark pedestrian area in the image.The L-HOG was used to quickly extract pedestrian feature, and additive kernel support vector machine (AK-SVM) was used to efficiently classify detected objects.Analysis result shows that when 500 images including 832 pedestrians on personal computer are detected, the model detects 720 pedestrians correctly, the detection rate is 86.5%, the error rate is 4.1%, and the detection time is 39 ms.When 48 400 images including 988 pedestrians on vehicle pedestrian detection system based on BF609 are detected, the model detects 861 pedestrians correctly, misses 127 pedestrians and detects 13 pedestrians in error.The detection speed is 20 fps.Underthe premise of not reducing the detection rate, the proposed pedestrian detection model can reach satisfying detection speed and can be used in vehicle equipment of real-time pedestrian detection.

     

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