• DocumentCode
    1739657
  • Title

    Eigenspace-based human face detection

  • Author

    Rujie, Liu ; Baozong, Yuan

  • Author_Institution
    Inst. of Inf. Sci., Northern Jiaotong Univ., Beijing, China
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1305
  • Abstract
    An eigenspace based human face detection method is proposed. The distribution of human face patterns in image space is modeled by means of the Mahalanobis-based clustering method. The eigenspace decomposition approach for conditional probability density estimation includes both the distance measure between the sample and eigenspace and the measure of sample projection and cluster centroid which is more robust than the traditional probability density estimation method where only the latter distance is considered. Thus it can achieve better human face detection result
  • Keywords
    Gaussian processes; eigenvalues and eigenfunctions; face recognition; image sampling; object detection; parameter estimation; pattern clustering; probability; Gaussian density estimation; Mahalanobis-based clustering method; cluster centroid; conditional probability density estimation; distance measure; eigenspace based human face detection method; eigenspace decomposition; eigenspace-based human face detection; face recognition; human face patterns distribution; image space; sample projection; Clustering methods; Covariance matrix; Density measurement; Face detection; Face recognition; Gaussian distribution; Humans; Information science; Multidimensional systems; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-5747-7
  • Type

    conf

  • DOI
    10.1109/ICOSP.2000.891785
  • Filename
    891785