Vision based speech animation transferring with underlying anatomical structure

  • Authors:
  • Yuru Pei;Hongbin Zha

  • Affiliations:
  • National Laboratory on Machine Perception, Peking University, Beijing, P.R. China;National Laboratory on Machine Perception, Peking University, Beijing, P.R. China

  • Venue:
  • ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
  • Year:
  • 2006

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Abstract

We present a novel method to transfer speech animation recorded in low resolution videos onto realistic 3D facial models. Unsupervised learning is utilized on a speech video corpus to find underlying manifold of facial configurations. K-means clustering is applied on the low dimensional space to find key speaking-related facial shapes. With a small set of laser scanner captured 3D models related to the clustering centroid, the facial animation in 2D videos is transferred onto 3D shapes. Especially by virtue of a weak perspective projection model, the underlying mandible rotation is recovered from videos and is utilized to drive 3D skull movements. The adaption of a generic skull onto facial models is guided by a 2D image, Tissue Map. With parsimonious data requirements, our system realizes the animation transferring and gains a realistic rendering effect with the underlying anatomical structure.