• DocumentCode
    3318344
  • Title

    Better face detection with vanishing point-based image rectification

  • Author

    Tien-Lung Chang ; Ching-Ho Wang ; Jen-Hui Chuang

  • Author_Institution
    Dept. of Comput. Sci., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • fYear
    2013
  • fDate
    15-19 July 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper we propose a novel face detection method based on the vanishing point of vertical lines in the scene to improve system performance in a common surveillance application. While most existing face datasets and detection techniques are based on the assumption that the camera has a similar height as the target faces, in practical situations the camera may be installed at different heights. Such discrepancy often degrades the detection performance of algorithms based on learning with certain (e.g., frontal) face orientation. In this paper we propose a transformation to rectify face images (video frames) such that it is not necessary to collect training data of different face orientations. Furthermore, with the proposed method there is no need to perform complex camera calibration. The only required information is the vanishing point of vertical lines, which can often be estimated easily. Experiments show prominent improvements in face detection performance can be obtained with the proposed image transformation.
  • Keywords
    face recognition; learning (artificial intelligence); video cameras; video surveillance; complex camera calibration; face dataset; face detection method; face orientation; image transformation; learning; vanishing point-based image rectification; vertical lines vanishing point; video frames; video surveillance application; Adaptive optics; Cameras; Face; Face detection; Optical distortion; Optical imaging; Surveillance; Vanishing point; face detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo Workshops (ICMEW), 2013 IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Type

    conf

  • DOI
    10.1109/ICMEW.2013.6618328
  • Filename
    6618328