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Laser & Optoelectronics Progress, Volume. 58, Issue 2, 0210015(2021)

Pedestrian Detection Based on Combination of Candidate Region Location and HOG-CLBP Features

Jiao Yao* and Fengqin Yu
Author Affiliations
  • School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (9)
    Equations (0)
    References (23)
    Cited By (2)
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    Figures & Tables(9)
    Flow chart of proposed algorithm

    Fig. 1. Flow chart of proposed algorithm

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    Candidate region windows generated by different methods. (a) Selective search strategy; (b) restriction of aspect ratio

    Fig. 2. Candidate region windows generated by different methods. (a) Selective search strategy; (b) restriction of aspect ratio

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    Recognition rate and time of PCA-HOG in different dimensions. (a) Identification rate; (b) time

    Fig. 3. Recognition rate and time of PCA-HOG in different dimensions. (a) Identification rate; (b) time

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    Recognition rate and time of PCA-CLBP in different dimensions. (a) Identification rate; (b) time

    Fig. 4. Recognition rate and time of PCA-CLBP in different dimensions. (a) Identification rate; (b) time

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    Comparison of DET curves of different algorithms

    Fig. 5. Comparison of DET curves of different algorithms

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    Detection results of proposed algorithm on some images

    Fig. 6. Detection results of proposed algorithm on some images

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    • Table 1. Recognition rate and recognition speed of PCA-HOG in different dimensions

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      Table 1. Recognition rate and recognition speed of PCA-HOG in different dimensions

      PCA-HOG dimension203040506080100200300
      Recognition rate0.89000.92070.92080.91990.92110.92270.91860.91830.9181
      Time /s0.12900.14000.16700.35300.56400.76601.50702.03304.3040

    • Table 2. Recognition rate and recognition speed of PCA-CLBP in different dimensions

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      Table 2. Recognition rate and recognition speed of PCA-CLBP in different dimensions

      PCA-CLBP dimension123457102030
      Recognition rate0.76290.77940.79640.80230.80230.80290.79510.79500.7948
      Time /s0.11030.11570.12090.12520.14670.19550.25340.56840.9430

    • Table 3. Recognition rate and recognition speed of different algorithms

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      Table 3. Recognition rate and recognition speed of different algorithms

      AlgorithmRecognition rate /%Test time per image /s
      Ref.[2]89.008.560
      Ref.[6]94.703.500
      Ref.[10]90.100.008
      Ref.[11]75.340.460
      Ref.[22]93.507.200
      Ref.[23]93.603.870
      Proposed algorithm96.701.960
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    Jiao Yao, Fengqin Yu. Pedestrian Detection Based on Combination of Candidate Region Location and HOG-CLBP Features[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0210015

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    Paper Information

    Category: Image Processing

    Received: Jun. 8, 2020

    Accepted: Jul. 16, 2020

    Published Online: Jan. 5, 2021

    The Author Email: Yao Jiao (1013836707@qq.com)

    DOI:10.3788/LOP202158.0210015

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology