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Perceiving Systems Conference Paper 1995

Recognizing facial expressions under rigid and non-rigid facial motions using local parametric models of image motion

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Perceiving Systems
Michael Black
Director
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his work explores the use of local parametrized models of image motion for recovering and recognizing the non-rigid and articulated motion of human faces. Parametric flow models (for example affine) are popular for estimating motion in rigid scenes. We observe that within local regions in space and time, such models not only accurately model non-rigid facial motions but also provide a concise description of the motion in terms of a small number of parameters. These parameters are intuitively related to the motion of facial features during facial expressions and we show how expressions such as anger, happiness, surprise, fear, disgust, and sadness can be recognized from the local parametric motions in the presence of significant head motion. The motion tracking and expression recognition approach performed with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.

Author(s): Black, M. J. and Yacoob, Y.
Links:
Book Title: International Workshop on Automatic Face- and Gesture-Recognition
Year: 1995
Month: July
Bibtex Type: Conference Paper (inproceedings)
Address: Zurich
Electronic Archiving: grant_archive

BibTex 

@inproceedings{Black:IWAFGR:1995,
  title = {Recognizing facial expressions under rigid and non-rigid facial motions using local parametric models of image motion},
  booktitle = {International Workshop on Automatic Face- and Gesture-Recognition},
  abstract = {his work explores the use of local parametrized models of image motion for recovering and recognizing the non-rigid and articulated motion of human faces. Parametric flow models (for example affine) are popular for estimating motion in rigid scenes. We observe that within local regions in space and time, such models not only accurately model non-rigid facial motions but also provide a concise description of the motion in terms of a small number of parameters. These parameters are intuitively related to the motion of facial features during facial expressions and we show how expressions such as anger, happiness, surprise, fear, disgust, and sadness can be recognized from the local parametric motions in the presence of significant head motion. The motion tracking and expression recognition approach performed with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.},
  address = {Zurich},
  month = jul,
  year = {1995},
  slug = {black-iwafgr-1995},
  author = {Black, M. J. and Yacoob, Y.},
  month_numeric = {7}
}