Robust shape-based head tracking

  • Authors:
  • Yunshu Hou;Hichem Sahli;Ravyse Ilse;Yanning Zhang;Rongchun Zhao

  • Affiliations:
  • Joint Research Group on Audio Visual Signal Processing, Vrije Universiteit Brussel, Department ETRO, Brussel and Northwestern Polytechnical University, School of Computer Science, Xi'an, P.R. Chin ...;Joint Research Group on Audio Visual Signal Processing, Vrije Universiteit Brussel, Department ETRO, Brussel;Joint Research Group on Audio Visual Signal Processing, Vrije Universiteit Brussel, Department ETRO, Brussel;Joint Research Group on Audio Visual Signal Processing, Northwestern Polytechnical University, School of Computer Science, Xi'an, P.R. China;Joint Research Group on Audio Visual Signal Processing, Northwestern Polytechnical University, School of Computer Science, Xi'an, P.R. China

  • Venue:
  • ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
  • Year:
  • 2007

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Abstract

This work presents a new method to automatically locate frontal facial feature points under large scene variations (illumination, pose and facial expressions). First, we use a kernel-based tracker to detect and track the facial region in an image sequence. Then the results of the face tracking, i.e. face region and face pose, are used to constrain prominent facial feature detection and tracking. In our case, eyes and mouth corners are considered as prominent facial features. In a final step, we propose an improvement to the Bayesian Tangent Shape Model for the detection and tracking of the full shape model. A constrained regularization algorithm is proposed using the head pose and the accurately aligned prominent features to constrain the deformation parameters of the shape model. Extensive experiments demonstrate the accuracy and effectiveness of our proposed method.