Institute Homepage
Institute Homepage DE Sign In

Back

Perceiving Systems Conference Paper 1995

Tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion

pdf video publisher site
Thumb ticker sm headshot2021
Perceiving Systems
Michael Black
Director
Bildschirmfoto 2013 01 14 um 11.24.02

This paper 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 performs 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: Fifth International Conf. on Computer Vision, ICCV’95
Pages: 347-381
Year: 1995
Month: June
Bibtex Type: Conference Paper (inproceedings)
Address: Boston, MA
Electronic Archiving: grant_archive

BibTex 

@inproceedings{Yacoob:ICCV:1995,
  title = {Tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion},
  booktitle = {Fifth International Conf. on Computer Vision, ICCV'95},
  abstract = {This paper 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 performs with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.},
  pages = {347-381},
  address = {Boston, MA},
  month = jun,
  year = {1995},
  slug = {yacoob-iccv-1995},
  author = {Black, M. J. and Yacoob, Y.},
  month_numeric = {6}
}