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Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1815016(2022)

Small Target Accurate Vehicle Detection Algorithm Based on Improved Transformer

Guangda Xie1...2, Yang Li2,*, Hongquan Qu2 and Zaiming Sun3 |Show fewer author(s)
Author Affiliations
  • 1School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China
  • 2Information College, North China University of Technology, Beijing 100144, China
  • 3School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
    Equations (7)
    References (14)
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    Figures & Tables(10)
    Overall architecture of image enhancement model

    Fig. 1. Overall architecture of image enhancement model

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    Generator (G) (up) and Transformer block (down)

    Fig. 2. Generator (G) (up) and Transformer block (down)

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    Edge-enhancement network

    Fig. 3. Edge-enhancement network

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    Swin Transformer detection process

    Fig. 4. Swin Transformer detection process

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    Swin Transformer block and SW-MSA. (a) Swin Transformer block; (b) W-MSA; (c) SW-MSA

    Fig. 5. Swin Transformer block and SW-MSA. (a) Swin Transformer block; (b) W-MSA; (c) SW-MSA

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    Vehicle detection process

    Fig. 6. Vehicle detection process

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    Examples of UA-DETRAC dataset

    Fig. 7. Examples of UA-DETRAC dataset

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    Training process of Swin Transformer and proposed model. (a) Swin Transformer; (b) proposed model

    Fig. 8. Training process of Swin Transformer and proposed model. (a) Swin Transformer; (b) proposed model

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    Contrast of sharpness and detection effect between original image and image enhancement. (a) (b) (c) (d) Illumination change; (e) (f) (g) (h) blurred, dense small targets; (i) (j) (k) (l) long range small targets

    Fig. 9. Contrast of sharpness and detection effect between original image and image enhancement. (a) (b) (c) (d) Illumination change; (e) (f) (g) (h) blurred, dense small targets; (i) (j) (k) (l) long range small targets

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    • Table 1. Comparison results of different detection algorithm performance

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      Table 1. Comparison results of different detection algorithm performance

      TestsetModelBackboneAP /%Time /ms
      UA-DETRACCascade R-CNNResNet-10179.848.8
      UA-DETRACYOLOV3Darknet-5387.642.3
      UA-DETRACSwin-TransformerSwin-T96.465.3
      UA-DETRACProposed modelEnhance-Swin-T99.068.4
      VOC-vehicleCascade R-CNNResNet-10186.748.8
      VOC-vehicleYOLOV3Darknet-5390.942.3
      VOC-vehicleSwin-TransformerSwin-T95.265.3
      VOC-vehicleProposed modelEnhance-Swin-T98.168.4
      Small-100Cascade R-CNNResNet-10149.348.8
      Small-100YOLOV3Darknet-5357.942.3
      Small-100Swin-TransformerSwin-T80.465.3
      Small-100Proposed modelEnhance-Swin-T88.368.4
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    Guangda Xie, Yang Li, Hongquan Qu, Zaiming Sun. Small Target Accurate Vehicle Detection Algorithm Based on Improved Transformer[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1815016

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    Paper Information

    Category: Machine Vision

    Received: Jun. 11, 2021

    Accepted: Sep. 2, 2021

    Published Online: Aug. 30, 2022

    The Author Email: Yang Li (2442590777@qq.com)

    DOI:10.3788/LOP202259.1815016

    Topics

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