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SUN Y B,WANG R,ZHANG Q,et al. A cross-modality person re-identification method for visible-infrared images[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(6):2018-2025 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0554
Citation: SUN Y B,WANG R,ZHANG Q,et al. A cross-modality person re-identification method for visible-infrared images[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(6):2018-2025 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0554

A cross-modality person re-identification method for visible-infrared images

doi: 10.13700/j.bh.1001-5965.2022.0554
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  • Corresponding author: E-mail:dbdxwangrong@163.com
  • Received Date: 29 Jun 2022
  • Accepted Date: 29 Jun 2022
  • Available Online: 09 Sep 2022
  • Publish Date: 06 Sep 2022
  • We propose a cross-modality person re-identification strategy for visible-infrared images, which aims to lower the sensitivity of the model to image color information and narrow the difference between visible and infrared modalities. First, the visible image is transformed into HSV color space, and the V component, which only describes the light and dark information of the image, is extracted to reduce the dependence of the model on color information. Second, to lessen the disparity between the modalities, a lightweight network downscales and upscales the V component image to provide an intermediate modality between visible and infrared images. Finally, evaluated on the SYSU-MM01 and RegDB datasets, The values of Rank-1 is improved by 6.67% and 1.18%, the values of mAP is improved by 6.47% and 1.15%, and mINP is improved by 5.59% and 0.42%, respectively.

     

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