Integrating Face and Gait for Human Recognition

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{bb52076,
  author =       "Xiaoli Zhou and Bir Bhanu",
  title =        "Integrating Face and Gait for Human Recognition",
  booktitle =    "Computer Vision and Pattern Recognition Workshop",
  year =         "2006",
  pages =        "55",
  month =        "17-22 " # jun,
  publisher =    "IEEE",
  bibsource =    "http://iris.usc.edu/Vision-Notes/bibliography/motion-f738.html#TT49185",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CVPRW.2006.103",
  abstract =     "This paper introduces a new video based recognition
                 method to recognise non-cooperating individuals at a
                 distance in video, who expose side views to the camera.
                 Information from two biometric sources, side face and
                 gait, is used and integrated for recognition. For side
                 face, we construct Enhanced Side Face Image (ESFI), a
                 higher resolution image compared with the image
                 directly obtained from a single video frame, to fuse
                 information of face from multiple video frames. For
                 gait, we use Gait Energy Image (GEI), a spatio-temporal
                 compact representation of gait in video, to
                 characterise human walking properties. The features of
                 face and the features of gait are obtained separately
                 using Principal Component Analysis (PCA) and Multiple
                 Discriminant Analysis (MDA) combined method from ESFI
                 and GEI, respectively. They are then integrated at
                 match score level. Our approach is tested on a database
                 of video sequences corresponding to 46 people. The
                 different fusion methods are compared and analysed. The
                 experimental results show that (a) Integrated
                 information from side face and gait is effective for
                 human recognition in video; (b) The idea of
                 constructing ESFI from multiple frames is promising for
                 human recognition in video and better face features are
                 extracted from ESFI compared to those from original
                 face images.",
  notes =        "on GP??",
}

Genetic Programming entries for Xiaoli Zhou Bir Bhanu

Citations