• DocumentCode
    3139730
  • Title

    Quantifying the Makeup Effect in Female Faces and Its Applications for Age Estimation

  • Author

    Ranran Feng ; Prabhakaran, Balakrishnan

  • Author_Institution
    Comput. Sci. Dept., Univ. of Texas at Dallas, Richardson, TX, USA
  • fYear
    2012
  • fDate
    10-12 Dec. 2012
  • Firstpage
    108
  • Lastpage
    115
  • Abstract
    In this paper, a comprehensive statistical study of makeup effect on facial parts (skin, eyes, and lip) is conducted first. According to the statistical study, a method to detect whether makeup is applied or not based on input facial image is proposed, then the makeup effect is further quantified as Young Index (YI) for female age estimation. An age estimator with makeup effect considered is presented in this paper. Results from the experiments find that with the makeup effect considered, the method proposed in this paper can improve accuracy by 0.9-6.7% in CS (Cumulative Score) and 0.26-9.76 in MAE (Mean of Absolute Errors between the estimated age and the ground truth age labeled or acquired from the data) comparing with other age estimation methods.
  • Keywords
    estimation theory; face recognition; statistical analysis; MAE; YI; Young index; absolute errors mean; age estimation; facial parts makeup effect; female age estimation; female face makeup effect; input facial image; makeup detection; statistical study; Accuracy; Correlation; Detectors; Estimation; Image color analysis; Image edge detection; Skin; Age Estimation; Makeup Detection; Makeup Quantification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia (ISM), 2012 IEEE International Symposium on
  • Conference_Location
    Irvine, CA
  • Print_ISBN
    978-1-4673-4370-1
  • Type

    conf

  • DOI
    10.1109/ISM.2012.29
  • Filename
    6424642