• DocumentCode
    3660161
  • Title

    Facial memorability prediction fusing geometric and texture features

  • Author

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

  • Author_Institution
    College of Computer Science &
  • fYear
    2015
  • Firstpage
    998
  • Lastpage
    1002
  • 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 sum-of-squares error to analyze the correlation and error of the predicted memorability score with ground truth.
  • Keywords
    "Mouth","Feature extraction","Computer vision","Shape","Correlation","Conferences","Predictive models"
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICInfA.2015.7279432
  • Filename
    7279432