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Proceedings Paper

Facial feature tracking with the super image vector inner product
Author(s): Wei Su; Laurence G. Hassebrook; S. Hariharan
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Paper Abstract

We overview a technique known as Super Image Vector Inner Product as applied to Facial pose estimation. The method is mathematically similar to correlation based methods but is numerically more efficient. The Vector Inner Product approach attains its pose and position estimation by embedding these distortions in its phase response. We demonstrate for the first time, that that the Super Image Vector Inner Product can be used for facial identification. We present a method by which segmenting the face into a set of feature regions, individual Super Images can be combined together using mesh techniques to track facial expressions.

Paper Details

Date Published: 7 May 2007
PDF: 11 pages
Proc. SPIE 6566, Automatic Target Recognition XVII, 656618 (7 May 2007); doi: 10.1117/12.719615
Show Author Affiliations
Wei Su, Univ. of Kentucky (United States)
Laurence G. Hassebrook, Univ. of Kentucky (United States)
S. Hariharan, Univ. of Kentucky (United States)

Published in SPIE Proceedings Vol. 6566:
Automatic Target Recognition XVII
Firooz A. Sadjadi, Editor(s)

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