Mar 27, 2013

Simultaneous facial feature tracking and facial expression recognition

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Yongqiang LiQiang Ji

Abstract

The tracking and recognition of facial activities from images or videos have attracted great attention in computer vision field. Facial activities are characterized by three levels. First, in the bottom level, facial feature points around each facial component, i.e., eyebrow, mouth, etc., capture the detailed face shape information. Second, in the middle level, facial action units, defined in the facial action coding system, represent the contraction of a specific set of facial muscles, i.e., lid tightener, eyebrow raiser, etc. Finally, in the top level, six prototypical facial expressions represent the global facial muscle movement and are commonly used to describe the human emotion states. In contrast to the mainstream approaches, which usually only focus on one or two levels of facial activities, and track (or recognize) them separately, this paper introduces a unified probabilistic framework based on the dynamic Bayesian network to simultaneously and coherently represent the facial evolvement in different levels, their interactions and their observations. Advanced machine learning methods are introduced to learn the model based on both training data and subjective prior knowledge. Given the model and the measurements of fac...Continue Reading

  • References12
  • Citations6

References

  • References12
  • Citations6

Citations

Mentioned in this Paper

Face
Facial Expression
Biometric Identification
Contraction (Finding)
Optical Image Reconstruction
Bayesian Prediction
Entire Eyebrow
Raiser
Eyebrow Structure
Facial Muscles

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