• DocumentCode
    3752250
  • Title

    Detection of facial parts via deformable part model using part annotation

  • Author

    Kazuhiro Nishida;Naoko Enami;Yasuo Ariki

  • Author_Institution
    Graduate School of System Informatics, Kobe University, Japan
  • fYear
    2015
  • Firstpage
    192
  • Lastpage
    195
  • Abstract
    In this paper, we propose a novel method for facial parts detection based on Deformable Part Model (DPM). In DPM, the parts are useful regions to detect the face and do not always correspond to the facial parts such as eye, nose and mouth. We model facial parts as a part filter and use annotation to training the position and size. In addition, we discuss the algorithm to deal with the variation of bounding box in the annotation. Our experimental results show that the proposed algorithm improves DPM for facial parts detection.
  • Keywords
    "Face","Mouth","Nose","Training","Deformable models","Face detection","Electronic mail"
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2015 Asia-Pacific
  • Type

    conf

  • DOI
    10.1109/APSIPA.2015.7415501
  • Filename
    7415501