Real-time View-based Face Alignment using Active Wavelet Networks

  • Authors:
  • Changbo Hu;Rogerio Feris;Matthew Turk

  • Affiliations:
  • -;-;-

  • Venue:
  • AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
  • Year:
  • 2003

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Abstract

The Active Wavelet Network (AWN) [9] approach was recently proposedfor automatic face alignment, showing advantages over ActiveAppearance Models (AAM), such as more robustness against partialocclusions and illumination changes. In this paper, we (1) extendthe AWN method to a view-based approach, (2) verify the robustnessof our algorithm with respect to unseen views in a large datasetand (3)show that using only nine wavelets, our method yieldssimilar performance to state-of-the-art face alignment systems,with a significant enhancement in terms of speed. Afteroptimization, our system requires only 3ms per iteration on a1.6GHz Pentium IV. We show applications in face alignment forrecognition and real-time facial feature tracking underlarge posevariations.