• Laser & Optoelectronics Progress
  • Vol. 55, Issue 11, 111007 (2018)
Qing Tian1, Tongyang Yuan1、*, Dan Yang1, and Yun Wei2
Author Affiliations
  • 1 School of Electronic Information Engineering, North China University of Technology, Beijing 100144, China
  • 2 Beijing Urban Construction Design & Development Group Co., Ltd., Beijing 100037, China;
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    DOI: 10.3788/LOP55.111007 Cite this Article Set citation alerts
    Qing Tian, Tongyang Yuan, Dan Yang, Yun Wei. A Pedestrian Detection Method Based on Dark Channel Defogging and Deep Learning[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111007 Copy Citation Text show less
    Structure of ZF network
    Fig. 1. Structure of ZF network
    Structure of RPN
    Fig. 2. Structure of RPN
    (a) Sample label image; (b) label file in XML
    Fig. 3. (a) Sample label image; (b) label file in XML
    Flow chart of dark channel defogging algorithm
    Fig. 4. Flow chart of dark channel defogging algorithm
    Flow chart of Faster R-CNN training algorithm
    Fig. 5. Flow chart of Faster R-CNN training algorithm
    (a) (b) Original images; (c)(d) image processed by dark channel defogging algorithm
    Fig. 6. (a) (b) Original images; (c)(d) image processed by dark channel defogging algorithm
    (a)(c) Test results of model 1; (b)(d) test results of model 2
    Fig. 7. (a)(c) Test results of model 1; (b)(d) test results of model 2
    (a)(c)(e) Test results of model 1; (b)(d)(f) test results of model 2
    Fig. 8. (a)(c)(e) Test results of model 1; (b)(d)(f) test results of model 2
    (a) Test results 1 of model 1; (b) test results 2 of model 1
    Fig. 9. (a) Test results 1 of model 1; (b) test results 2 of model 1
    (a) Test results 1 of model 2; (b) test results 2 of model 2
    Fig. 10. (a) Test results 1 of model 2; (b) test results 2 of model 2
    Evaluation indexTest sample
    Poor qualitytest pictureFog testpictureAverage results withtest image enhancementAverage results withouttest image enhancement
    Detection rate of model 190889089
    Detection rate of model 2939092.591.5
    Flse alarm rate of model 1585.57
    False alarm rate of model 22534
    Table 1. Detection rate and false alarm rate of model 1 and model 2%
    ModelPixel size
    500×375500×333640×4801280×720
    Detection time of model 1 /s2.380912.455012.478092.490890
    Detection time of model 2 /s2.370172.454962.470912.480745
    Table 2. Detection time of model 1 and model 2
    Qing Tian, Tongyang Yuan, Dan Yang, Yun Wei. A Pedestrian Detection Method Based on Dark Channel Defogging and Deep Learning[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111007
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