• DocumentCode
    2054778
  • Title

    Locating Nosetips and Estimating Head Pose in Images by Tensorposes

  • Author

    Tu, Jilin ; Huang, Thomas

  • Author_Institution
    Illinois Univ., Urbana
  • Volume
    4
  • fYear
    2007
  • fDate
    Sept. 16 2007-Oct. 19 2007
  • Abstract
    This paper introduces a head pose estimation system that localizes nose-tip of the faces and estimate head poses in images simultaneously. After the nose-tip in the training data are manually labeled, the appearance variation caused by head pose changes is characterized by tensor model. Given images with unknown head pose and nose-tip location, the nose-tip of the face is localized in a coarse-to-fine fashion, and the head pose can be estimated simultaneously. We evaluated our system on the Pointing´04 head pose image database with 50% of the data as training set and the rest as testing set. With the nose-tip location provided, our head pose estimators can achieve 94% head pose classification accuracy(within plusmn15deg). With nose-tip automatically localized, we achieves 85% nose-tip localization accuracy(within 3 pixels from the ground truth), and 81% head pose classification accuracy (within plusmn15deg).
  • Keywords
    face recognition; human computer interaction; image classification; pose estimation; tensors; face recognition; head pose estimation system; human computer interaction; image classification; image database; nose-tip localization; tensor model; Eyes; Face detection; Head; Humans; Image databases; Image resolution; Nose; Tensile stress; Testing; Training data; Head Pose; Tensor; nose-tip localization; pointing04;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2007. ICIP 2007. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1437-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2007.4380067
  • Filename
    4380067