• Laser & Optoelectronics Progress
  • Vol. 57, Issue 18, 181007 (2020)
Ke Wu1, Baohua Zhang1、*, Xiaoqi Lü2, Yu Gu1, Yueming Wang1, Xin Liu1, Yan Ren1, Jianjun Li1, and Ming Zhang1
Author Affiliations
  • 1School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 0 14010, China
  • 2College of Information Engineering, Inner Mongolia University of Technology, Huhehot, Inner Mongolia 0 10080, China
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    DOI: 10.3788/LOP57.181007 Cite this Article Set citation alerts
    Ke Wu, Baohua Zhang, Xiaoqi Lü, Yu Gu, Yueming Wang, Xin Liu, Yan Ren, Jianjun Li, Ming Zhang. Person Re-Identification Based on Squeeze and Excitation Residual Neural Network and Feature Fusion[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181007 Copy Citation Text show less
    Modules of SE-ResNet and ResNet
    Fig. 1. Modules of SE-ResNet and ResNet
    Activation functions of ReLU and Leaky ReLU. (a) ReLU; (b) Leaky ReLU
    Fig. 2. Activation functions of ReLU and Leaky ReLU. (a) ReLU; (b) Leaky ReLU
    Structure diagram of SE-ResNet
    Fig. 3. Structure diagram of SE-ResNet
    Effect diagram of improved SE-ResNet pedestrian re-identification algorithm
    Fig. 4. Effect diagram of improved SE-ResNet pedestrian re-identification algorithm
    Partial pedestrian images in two datasets. (a) DukeMTMC-reID dataset; (b) MarKet-1501 dataset
    Fig. 5. Partial pedestrian images in two datasets. (a) DukeMTMC-reID dataset; (b) MarKet-1501 dataset
    Rank-k and mAPs at different fusion schemes. (a) Rank-k; (b) mAP
    Fig. 6. Rank-k and mAPs at different fusion schemes. (a) Rank-k; (b) mAP
    Convolution kernel sizeRank-1 /%Rank-5 /%Rank-10 /%mAP /%Running time /s
    3×391.6095.6096.4087.801316
    5×592.1095.4096.3087.901807
    7×793.1096.0097.0089.001983
    9×991.7495.7297.0087.5912273
    11×1191.7495.7297.0087.5914146
    Table 1. Experimental results of different convolution sizes
    AlgorithmRank-1Rank-5Rank-10mAP
    DenseNet-121[13]90.1794.5096.0874.02
    PCB[14]92.6493.3794.9577.47
    ResNet5088.8494.8496.6271.59
    SE-ResNet(before fusion)88.5393.2894.8982.25
    SE-ResNet(after fusion)93.1096.0097.0089.00
    Table 2. Performance comparison of different algorithms (Market-1501 dataset)unit: %
    AlgorithmRank-1Rank-5Rank-10mAP
    PCB85.6891.4793.4980.68
    DenseNet-12180.0288.8691.7463.63
    ResNet5085.5991.3892.2680.65
    SE-ResNet(before fusion)57.9469.7074.5946.75
    SE-ResNet(after fusion)86.0091.4294.0381.24
    Table 3. Performance comparison of different algorithms (DukeMTMC-reID dataset) unit: %
    Ke Wu, Baohua Zhang, Xiaoqi Lü, Yu Gu, Yueming Wang, Xin Liu, Yan Ren, Jianjun Li, Ming Zhang. Person Re-Identification Based on Squeeze and Excitation Residual Neural Network and Feature Fusion[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181007
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