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Laser & Optoelectronics Progress, Volume. 57, Issue 18, 181026(2020)

Facial Expression Recognition Method of Spinner Based on Eye Data

Jingfeng Shao* and Haiqiang Feng
Author Affiliations
  • School of Management, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
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    References (15)
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    Figures & Tables(10)
    Key points

    Fig. 1. Key points

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    Image preprocessing process

    Fig. 2. Image preprocessing process

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    Eye data set

    Fig. 3. Eye data set

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    Inception-v3 network structure

    Fig. 4. Inception-v3 network structure

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    Accuracy curve

    Fig. 5. Accuracy curve

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    Loss curve

    Fig. 6. Loss curve

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    Test results

    Fig. 7. Test results

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    Comparison of image recognition accuracy after different processing. (a) Eye interception; (b) image preprocessing; (c) our method

    Fig. 8. Comparison of image recognition accuracy after different processing. (a) Eye interception; (b) image preprocessing; (c) our method

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    • Table 1. Sample data

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      Table 1. Sample data

      SamplenumberWorkingtime /hFinenessunevenness /%Number ofthin nodeper kmNumber ofthick nodeper kmNumber of3-mm hairinessper mBreakingstrength /(10-2 N·tex-1)Breakingelongation /%
      1121.797562192.345.918.77
      1221.747562192.646.038.78
      1321.897632292.75.928.79
      1421.877632101.985.948.79
      1521.977672183.86.048.88
      1622.087582174.386.158.67
      1721.957642135.476.058.84
      1821.947652192.416.078.87
      2121.977452101.965.988.90
      2221.817522202.036.128.76
      2321.957482152.415.968.82
      2421.927522202.356.18.91
      2522.057582172.365.898.75
      2621.877562151.865.948.75
      2721.947562182.045.998.64
      2822.087562212.416.118.77
      3122.057522162.335.968.94
      3222.067612233.145.888.64
      3321.977602242.856.018.59
      3421.867502202.535.948.88
      3522.077522242.636.088.75
      3621.967642181.785.848.83
      3721.947622252.675.928.79
      3822.017562183.126.048.79

    • Table 2. Weight proportion of yarn index influence for the expression of the spinner%

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      Table 2. Weight proportion of yarn index influence for the expression of the spinner%

      Sample numberWeight
      FinenessunevennessNumber ofthin nodeNumber ofthick nodeNumber of3-mm hairinessBreakingstrengthBreakingelongation
      10009900
      20029421
      30019811
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    Jingfeng Shao, Haiqiang Feng. Facial Expression Recognition Method of Spinner Based on Eye Data[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181026

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    Paper Information

    Category: Image Processing

    Received: Mar. 19, 2020

    Accepted: Apr. 23, 2020

    Published Online: Sep. 2, 2020

    The Author Email: Shao Jingfeng (shaojingfeng1980@aliyun.com)

    DOI:10.3788/LOP57.181026

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology