• Laser & Optoelectronics Progress
  • Vol. 58, Issue 4, 0411003 (2021)
Hao Zhan1、2、3、*, Zhencai Zhu1、2、3, Yonghe Zhang1、2、3, Ming Guo1、2, and Guopeng Ding1、2
Author Affiliations
  • 1Innovation Academy for Microsatellite, Chinese Academy of Sciences, Shanghai 201203, China
  • 2Key Laboratory of Microsatellites, Chinese Academy of Sciences, Shanghai 201203, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    DOI: 10.3788/LOP202158.0411003 Cite this Article Set citation alerts
    Hao Zhan, Zhencai Zhu, Yonghe Zhang, Ming Guo, Guopeng Ding. Loop-Closure Detection Using Image Sequencing Based on ResNet[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0411003 Copy Citation Text show less
    Flowchart of the proposed algorithm
    Fig. 1. Flowchart of the proposed algorithm
    Typical ResNet18 structure
    Fig. 2. Typical ResNet18 structure
    Designed ResNet structure
    Fig. 3. Designed ResNet structure
    Direct output form of designed network
    Fig. 4. Direct output form of designed network
    Typical images in different datasets. (a) City Centre; (b) New College
    Fig. 5. Typical images in different datasets. (a) City Centre; (b) New College
    GPS data. (a) City Centre; (b) New College
    Fig. 6. GPS data. (a) City Centre; (b) New College
    Comparison of P-R curves of proposed algorithm, different layers in ResNet18, and other algorithms. (a) City Centre; (b) New College
    Fig. 7. Comparison of P-R curves of proposed algorithm, different layers in ResNet18, and other algorithms. (a) City Centre; (b) New College
    Form of output combination
    Fig. 8. Form of output combination
    Influence of different sequence lengths on the results. (a) City Centre; (b) New College
    Fig. 9. Influence of different sequence lengths on the results. (a) City Centre; (b) New College
    Influence of different m on the results when the sequence length is 15 in City Centre dataset
    Fig. 10. Influence of different m on the results when the sequence length is 15 in City Centre dataset
    Similarity curves before and after combination of 15 length sequences. (a) Similarity between sequence combination features and other frames; (b) similarity of sequence without combination
    Fig. 11. Similarity curves before and after combination of 15 length sequences. (a) Similarity between sequence combination features and other frames; (b) similarity of sequence without combination
    ParameterSymbolValue
    Number of frames not detectedl50
    Number of frames in the intervalls7
    Group length/framelw15
    Overlap length/frameNo3
    Number of matching pointsNd12
    Table 1. Setting of some parameters
    Hao Zhan, Zhencai Zhu, Yonghe Zhang, Ming Guo, Guopeng Ding. Loop-Closure Detection Using Image Sequencing Based on ResNet[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0411003
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