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Physiognomy in New Era: A Survey of Automatic Personality Prediction Based on Facial Image

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Abstract

At present, personality computing technology facilitates the understanding, prediction, and management of human behavior. With the increasing importance of faces in personal daily assessments, establishing a relationship between facial morphological features and personality traits is a major breakthrough in personality computing technology. This paper is a survey of such technology of automatic personality prediction based on face and it aims at providing not only a solid knowledge base about the state-of-the-art in automatic personality prediction, but also to provide a conceptual model of automatic personality prediction, based on the literature. In addition, the analysis of the prediction results of the existing researches is emphasized, and there are still problems in the field, such as lack of information on research data, single age group of the sample population, incomplete design characteristics of the artificial design etc., and the potential applications and development directions are determined.

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Author information

Authors and Affiliations

  1. North China University of Science and Technology, Tangshan, 063210, China

    Xu Jia

  2. Northwestern Polytechnical University, Xi’An, 710129, China

    Xu Jia, Weijian Tian & Yangyu Fan

Authors
  1. Xu Jia
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  2. Weijian Tian
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  3. Yangyu Fan
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Corresponding author

Correspondence to Xu Jia .

Editor information

Editors and Affiliations

  1. Northwestern Polytechnical University, Xi′an, China

    Bo Li

  2. Northwestern Polytechnical University, Xi'an, China

    Mao Yang

  3. Shandong University, Jinan, Qinghai, China

    Hui Yuan

  4. Northwestern Polytechnical University, Xi'an, Shaanxi, China

    Zhongjiang Yan

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Jia, X., Tian, W., Fan, Y. (2019). Physiognomy in New Era: A Survey of Automatic Personality Prediction Based on Facial Image. In: Li, B., Yang, M., Yuan, H., Yan, Z. (eds) IoT as a Service. IoTaaS 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-14657-3_2

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  • DOI: https://doi.org/10.1007/978-3-030-14657-3_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14656-6

  • Online ISBN: 978-3-030-14657-3

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