• DocumentCode
    1689785
  • Title

    Effective distance measure for unusual facial expression detection of human face images

  • Author

    Wu, Hsien-Chu ; Lu, Lia-Hong

  • Author_Institution
    Grad. Sch. of Comput. Sci. & Inf. Technol., Nat. Taichung Inst. of Technol., Taichung, Taiwan
  • fYear
    2010
  • Firstpage
    18
  • Lastpage
    23
  • Abstract
    In this paper, a simple method for the facial expression detection to identify the normal and unusual of expression variations of the human face is proposed. The approach uses the binary edge image to present the shape of facial expression. The modified Hausdorff distance measure is adapted to our approach to compare between the unusual and normal face expression. In our algorithm, it just needs to use three face images per subject for training, which include two normal facial images and one unusual facial image to obtain individual thresholds for human face detection, respectively. Therefore, the proposed technique does not require a large number of images for training.
  • Keywords
    edge detection; emotion recognition; face recognition; shape recognition; Hausdorff distance measurement; binary edge image; effective distance measurement; facial expression shape; human face detection; human face images; unusual facial expression detection; Biomedical imaging; Detectors; Image recognition; Pixel; Variable speed drives; Hausdorff distance measures; binary edge image; facial expression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aware Computing (ISAC), 2010 2nd International Symposium on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4244-8313-6
  • Type

    conf

  • DOI
    10.1109/ISAC.2010.5670449
  • Filename
    5670449