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An Algorithm of Recommending Apposite ID Photos

Author

Listed:
  • Xuanang Feng

    (Nagoya University)

  • Miki Miyachi

    (Nagoya University)

  • Ziqi Zhu

    (Nagoya University)

  • Eisuke Kita

    (Nagoya University)

Abstract

This article proposes an algorithm to recommend apposite ID photos for users by judging the photo of which the facial expression is apposite or not as the ID photo. Microsoft’s Kinect sensor is used for taking photos. Parts of the face, such as eyes, nose, and mouth, are analyzed as explanatory variables for judging face expression. Some body coordinate information such as head and shoulders is used to trim the photos. Neural networks and support vector machines are employed and compared to our proposed method. To achieve accurate results, ten examinees including specialized staff are selected for taking ID photo used for training models. A series of experiments are conducted to examine the validity. As a result, the accuracy of neural networks is better than that of the support vector machine. Furthermore, we analyze and discuss the difference between system results and specialized staffs’ opinions.

Suggested Citation

  • Xuanang Feng & Miki Miyachi & Ziqi Zhu & Eisuke Kita, 2020. "An Algorithm of Recommending Apposite ID Photos," The Review of Socionetwork Strategies, Springer, vol. 14(1), pages 109-121, April.
    • Handle: RePEc:spr:trosos:v:14:y:2020:i:1:d:10.1007_s12626-019-00059-9
    DOI: 10.1007/s12626-019-00059-9
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