Laser & Optoelectronics Progress, Volume. 55, Issue 11, 111507(2018)

Loop Closure Detection Algorithm Based On Multi-Level Convolutional Neural Network Features

Zhenqiang Bao*, Aihua Li, Zhigao Cui, Yanzhao Su, and Yong Zheng
Author Affiliations
  • Institute of War Support, Rocket Force University of Engineering, Xi'an, Shannxi 710025, China
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    Figures & Tables(9)
    Flow of loop closure detection based on multi-level features
    Sample images of Gardens Point dataset. (a) Day_left; (b) day_right; (c) night_right
    Visualization of similarity matrix for Gardens Point dataset. (a) pool3+pool5+fc1; (b) pool1; (c) pool3; (d) fc1
    Precision-recall curve of different method on Gardens Point dataset
    Images taken at the same location but at different time
    Dynamic object detection results for YOLOv2. (a) Results of YOLOv2 method; (b) results of proposed method
    Flow of loop closure detection based on image dynamic interference semantic filter mechanism
    Precision-recall curve of different method on Tokyo24/7 dataset
    • Table 1. Structure of VGG19

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      Table 1. Structure of VGG19

      NumberLayerDimensionNumberLayerDimension
      1conv1_1321126413conv4_2401408
      2conv1_2321126414conv4_3401408
      3pool180281615conv4_4401408
      4conv2_1160563216pool4100352
      5conv2_1160563217conv5_1100352
      6pool240140818conv5_2100352
      7conv3_180281619conv5_3100352
      8conv3_280281620conv5_4100352
      9conv3_380281621pool525088
      10conv3_480281622fc14096
      11pool320070423fc24096
      12conv4_140140824fc31000
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    Zhenqiang Bao, Aihua Li, Zhigao Cui, Yanzhao Su, Yong Zheng. Loop Closure Detection Algorithm Based On Multi-Level Convolutional Neural Network Features[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111507

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    Paper Information

    Category: Machine Vision

    Received: Apr. 21, 2018

    Accepted: Jun. 6, 2018

    Published Online: Aug. 14, 2019

    The Author Email: Zhenqiang Bao (bzhenqiang@163.com)

    DOI:10.3788/LOP55.111507

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