Facial memorability prediction fusing geometric and texture features

Ziyi Dai, Zehua Pan, Yewei Wu, Linlin Shen, Qibin Hou

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

As different faces have different features, the degree of memorability of faces are different, which are named memorability in this paper. We mainly study the relation between the memorability and different features such as the geometrical features of the faces, the location of eyes, the size of mouth and eyes and the Histogram of Oriented Gradient (HOG). We use SVR model to regress the features of face images, and predict the memorability score. Finally, we use the spearman rank correlation coefficient and residual sumof- squares error to analyze the correlation and error of the predicted memorability score with ground truth.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages998-1002
Number of pages5
ISBN (Electronic)9781467391047
DOIs
Publication statusPublished - 28 Sep 2015
Externally publishedYes
Event2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics - Yunnan, China
Duration: 8 Aug 201510 Aug 2015

Publication series

Name2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics

Conference

Conference2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics
Country/TerritoryChina
CityYunnan
Period8/08/1510/08/15

Keywords

  • memorability
  • multiple features
  • SVR

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Computational Theory and Mathematics
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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