• Journal of Infrared and Millimeter Waves
  • Vol. 40, Issue 6, 870 (2021)
Huai-Qian LI1、2, Ming-Hui YANG1, and Liang WU1、*
Author Affiliations
  • 1Key Laboratory of Terahertz Solid State Technology,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences,Shanghai 200050,China
  • 2Center of Materials Science and Optoelectronics Engineering,University of Chinese Academy of Sciences,Beijing 100049,China
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    DOI: 10.11972/j.issn.1001-9014.2021.06.023 Cite this Article
    Huai-Qian LI, Ming-Hui YANG, Liang WU. High localization accuracy 3D object detection in active millimeter wave holographic images[J]. Journal of Infrared and Millimeter Waves, 2021, 40(6): 870 Copy Citation Text show less
    The structure of our proposed 3D concealed object detector for AMMW holographic images
    Fig. 1. The structure of our proposed 3D concealed object detector for AMMW holographic images
    Projection of the AMMW holographic image (a) AMMW holographic image, (b) the resulting 2D front view of performing projection along the Z axis of the holographic image in Fig. 2(a), (c) the shape and size changes caused by projecting a 3D object into 2D views
    Fig. 2. Projection of the AMMW holographic image (a) AMMW holographic image, (b) the resulting 2D front view of performing projection along the Z axis of the holographic image in Fig. 2(a), (c) the shape and size changes caused by projecting a 3D object into 2D views
    The structure of our proposed input module
    Fig. 3. The structure of our proposed input module
    The distribution of the number of points in the bounding box in 3D point clouds and 2D front images
    Fig. 4. The distribution of the number of points in the bounding box in 3D point clouds and 2D front images
    The structure of our proposed 3D feature extractor
    Fig. 5. The structure of our proposed 3D feature extractor
    The structure of our proposed output module
    Fig. 6. The structure of our proposed output module
    Comparison of localization and detection performance for different networks (a) Recall as a function of IOU threshold, (b) PR curve under IOU = 0.5
    Fig. 7. Comparison of localization and detection performance for different networks (a) Recall as a function of IOU threshold, (b) PR curve under IOU = 0.5
    Qualitative detection results of different networks, where the red bounding boxes denote the ground-truth, and the yellow bounding boxes denote the predicted results (a)-(d) Our proposed method, (e) RPN, (f) Faster RCNN, (g) RetinaNet, (h) TridentNet
    Fig. 8. Qualitative detection results of different networks, where the red bounding boxes denote the ground-truth, and the yellow bounding boxes denote the predicted results (a)-(d) Our proposed method, (e) RPN, (f) Faster RCNN, (g) RetinaNet, (h) TridentNet
    F1-score under different thresholds of the confidence
    Fig. 9. F1-score under different thresholds of the confidence
    网络组件卷积类型通道卷积核步长填充空洞率感受野特征图
    降采样模块SubMConv1631113(192,400,41)
    SubMConv1631115(192,400,41)
    SpConv3232117(96,200,21)
    SubMConv32311111(96,200,21)
    SpConv64321115(48,100,11)
    SubMConv64311123(48,100,11)
    SpConv1283(1,1,2)(1,1,0)131(48,100,5)
    分支1SubMConv128311139(48,100,5)
    SpConv128(1,1,3)(1,1,2)0139(48,100,2)
    分支2SubMConv12831(2,2,1)(2,2,1)47(48,100,5)
    SpConv128(1,1,3)(1,1,2)0147(48,100,2)
    分支3SubMConv12831(3,3,1)(3,3,1)55(48,100,5)
    SpConv128(1,1,3)(1,1,2)0155(48,100,2)
    Table 1. Details of convolutional layers of the 3D feature extractor
    网络结构上下文信息提取模块XY方向降采样步长AP50
    SECOND[11×872.28
    SECOND + HRF×473.87
    SECOND + CIE873.85
    SECOND + HRF + CIE474.44
    Table 2. Comparison of the AP with different network structures
    网络输入AP10AP20AP30AP40AP50平均APFA50Re50速度(FPS)
    RPN[72D82.3579.2674.1564.2648.5069.7036.6857.9923.0
    Faster RCNN[72D88.8887.5384.7678.7167.3381.4422.7467.514.7
    RetinaNet[142D89.6588.7686.2080.1165.4482.0324.5967.189.0
    TridentNet[172D91.3889.9087.0780.1064.8782.6623.5267.044.1
    SECOND[113D92.5691.7589.8784.9772.2886.2921.2474.6522.9
    本工作3D92.9792.0490.0285.3474.4486.9620.9676.2617.3
    Table 3. Comparison of detection performance on different Networks
    Huai-Qian LI, Ming-Hui YANG, Liang WU. High localization accuracy 3D object detection in active millimeter wave holographic images[J]. Journal of Infrared and Millimeter Waves, 2021, 40(6): 870
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