3D Constrained Local Model for rigid and non-rigid facial tracking

  • Authors:
  • Louis-Philippe Morency

  • Affiliations:
  • USC Institute for Creative Technologies, 12015 Waterfront Drive

  • Venue:
  • CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • Year:
  • 2012

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Abstract

We present 3D Constrained Local Model (CLM-Z) for robust facial feature tracking under varying pose. Our approach integrates both depth and intensity information in a common framework. We show the benefit of our CLM-Z method in both accuracy and convergence rates over regular CLM formulation through experiments on publicly available datasets. Additionally, we demonstrate a way to combine a rigid head pose tracker with CLM-Z that benefits rigid head tracking. We show better performance than the current state-of-the-art approaches in head pose tracking with our extension of the generalised adaptive view-based appearance model (GAVAM).