Model-based varying pose face detection and facial feature registration in video images

  • Authors:
  • Lixin Fan;Kah Kay Sung

  • Affiliations:
  • School of Computing, National University of Singapore, Singapore;School of Computing, National University of Singapore, Singapore

  • Venue:
  • MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
  • Year:
  • 2000

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Abstract

This paper presents an automatic method for simultaneous human face detection and facial feature registration from colour video images. At the first stage, we use a skin colour Gaussian model to identify possible face locations under varying pose. Secondly, we compare image patterns with a varying pose face model in terms of shape and texture differences, using a combined feature-texture similarity measure (FTSM). False detections from the first stage are eliminated by setting an appropriate FTSM threshold. Moreover, one can also register the facial features (eyes, nose and mouth) by aligning a prototype face with the unknown pose faces. Experimental results show that the proposed method can achieve reliable face detection and feature registration under various conditions, including different poses, face appearances, and lighting conditions.