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Laser & Optoelectronics Progress, Volume. 56, Issue 21, 211503(2019)

Heel-Strike Event Detection Algorithm Based on Convolutional Neural Networks

Zhuorong Li1, Kaixuan Wang1, Xinlong He1, Zhongliang Mi2, and Yunqi Tang1、*
Author Affiliations
  • 1School of Forensic Science, People's Public Security University of China, Beijing 100038, China
  • 2Shanghai Key Laboratory of Crime Scene Evidence, Shanghai 200083, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
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    References (29)
    Cited By (3)
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    Figures & Tables(11)
    Gait events within a gait cycle

    Fig. 1. Gait events within a gait cycle

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    Sample of 2-CSD-map

    Fig. 2. Sample of 2-CSD-map

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    Algorithm for generating CSD-maps

    Fig. 3. Algorithm for generating CSD-maps

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    Algorithm for normalization of CSD-maps

    Fig. 4. Algorithm for normalization of CSD-maps

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    Frame work of process

    Fig. 5. Frame work of process

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    Line chart of detection accuracy of n-CSD-maps

    Fig. 6. Line chart of detection accuracy of n-CSD-maps

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    Line chart of detection accuracy of n-CSD-maps obtained by PCA+SVM algorithm

    Fig. 7. Line chart of detection accuracy of n-CSD-maps obtained by PCA+SVM algorithm

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    Histogram comparison of detection accuracy of CNN and SVM algorithms

    Fig. 8. Histogram comparison of detection accuracy of CNN and SVM algorithms

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    ROC curves of different angles. (a) 54°; (b) 72°; (c) 90°; (d) 108°; (e) 126°

    Fig. 9. ROC curves of different angles. (a) 54°; (b) 72°; (c) 90°; (d) 108°; (e) 126°

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    ROC curves from all angles

    Fig. 10. ROC curves from all angles

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    • Table 1. Confusion matrix when 6-CSD is used to obtain detection accuracy of cross angle

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      Table 1. Confusion matrix when 6-CSD is used to obtain detection accuracy of cross angle

      Angle54°72°90°108°126°
      54°72°90°108°126°0.94320.94040.93480.93300.92760.92920.95580.93720.92520.91040.92740.94480.96500.94860.90280.92880.94320.94960.95880.92680.92300.93360.94140.94560.9520
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    Zhuorong Li, Kaixuan Wang, Xinlong He, Zhongliang Mi, Yunqi Tang. Heel-Strike Event Detection Algorithm Based on Convolutional Neural Networks[J]. Laser & Optoelectronics Progress, 2019, 56(21): 211503

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    Paper Information

    Category: Machine Vision

    Received: Apr. 1, 2019

    Accepted: May. 6, 2019

    Published Online: Nov. 2, 2019

    The Author Email: Yunqi Tang (tangyunqi@ppsuc.edu.cn)

    DOI:10.3788/LOP56.211503

    Topics

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