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Proceedings Paper

Pose estimation and transformation of faces
Author(s): Ashit Talukder; David P. Casasent
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Paper Abstract

A new technique is discussed to estimate the pose (orientation) of unknown human faces from 2D gray-scale images and then transform the unknown face to a reference pose using a nonlinear feature extraction procedure. This feature extraction scheme is known as the maximum representation and discrimination feature (MRDF) method. The MRDF is shown to provide good features for discrimination between classes that is useful for pose estimation, and for object representation that is useful for pose transformation of an unknown face. Our approach is computationally efficient and has numerous potential applications, including post-invariant face recognition.

Paper Details

Date Published: 6 October 1998
PDF: 12 pages
Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); doi: 10.1117/12.325803
Show Author Affiliations
Ashit Talukder, Carnegie Mellon Univ. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 3522:
Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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