Real-Time Facial Feature Tracking on a Mobile Device

  • Authors:
  • P. A. Tresadern;M. C. Ionita;T. F. Cootes

  • Affiliations:
  • School of Cancer and Enabling Sciences, Stopford Building, University of Manchester, Manchester, UK M13 9PT;School of Cancer and Enabling Sciences, Stopford Building, University of Manchester, Manchester, UK M13 9PT;School of Cancer and Enabling Sciences, Stopford Building, University of Manchester, Manchester, UK M13 9PT

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 2012

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Abstract

This paper presents an implementation of the Active Appearance Model that is able to track a face on a mobile device in real-time. We achieve this performance by discarding an explicit texture model, using fixed-point arithmetic for much of the computation, applying a sequence of models with increasing complexity, and exploiting a sparse basis projection via Haar-like features. Our results show that the Haar-like feature basis achieves similar performance to more traditional approaches while being more suitable for a mobile device. Finally, we discuss mobile applications of the system such as face verification, teleconferencing and human-computer interaction.