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Supervised Local Linear Embedding (SLLE) for facial paralysis image sequence analysis

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3 Author(s)
Shu He ; Univ. of Strathclyde, Glasgow ; Soraghan, J.J. ; O'Reilly, B.F.

This paper proposed a novel approach based on local linear embedding (LLE) for modeling and understanding the temporal behaviour from facial paralysis image sequences. LLE is sensitive to scaling, illumination and face pose. A Supervised LLE (SLLE) based on directed Hausdorff distance is proposed for aligning two image sets from the two sides of the face using one generalized embedding space. The embedded low dimensional manifolds represent the asymmetry of the facial motion regardless of the extrinsic facial asymmetry caused by the natural bilateral asymmetry, illumination and shadows. Experimental results demonstrate that our approach is more reliable than frame difference based methods and optical flow based methods without a significant increase in computational complexity.

Published in:

Multimedia and Expo, 2008 IEEE International Conference on

Date of Conference:

June 23 2008-April 26 2008