Head pose recommendation for taking good selfies

Yi Tsung Hsieh, Mei Chen Yeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We present a head-pose recommendation system that guides a user in how to best pose while taking a selfe. Given an input face image, the system finds the most attractive angle of the face and suggests how the pose should be adjusted. The recommendation results are determined adaptively to the appearance and initial pose of the input face. The user study shows the recommendation performance of the system is moderately related to the degree of conformity among the photographers' recommendations.

Original languageEnglish
Title of host publicationMUSA2 2017 - Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, co-located with MM 2017
PublisherAssociation for Computing Machinery, Inc
Pages55-60
Number of pages6
ISBN (Electronic)9781450355094
DOIs
Publication statusPublished - 2017 Oct 27
Event1st ACM MM Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, MUSA2 2017 - Mountain View, United States
Duration: 2017 Oct 27 → …

Publication series

NameMUSA2 2017 - Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, co-located with MM 2017

Other

Other1st ACM MM Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, MUSA2 2017
CountryUnited States
CityMountain View
Period17/10/27 → …

Keywords

  • Computational aesthetics
  • Pose recommendation
  • Selfe
  • Smart photography

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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  • Cite this

    Hsieh, Y. T., & Yeh, M. C. (2017). Head pose recommendation for taking good selfies. In MUSA2 2017 - Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, co-located with MM 2017 (pp. 55-60). (MUSA2 2017 - Proceedings of the Workshop on Multimodal Understanding of Social, Affective and Subjective Attributes, co-located with MM 2017). Association for Computing Machinery, Inc. https://doi.org/10.1145/3132515.3132518