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Proceedings Paper

Recognizing human eyes
Author(s): Peter W. Hallinan
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Paper Abstract

Steps are taken toward the automatic, intensity-based recognition of human faces by constructing a vision system to automatically detect frontally-viewed human eyes in real data. The eye is modeled using a deformable template that specifies a parameterized geometry and an intensity model. The fit of the template is measured by a cost-functional employing robust estimators, i.e., (alpha) -trimmed means and variances, to overcome highlights, shadows, nonrigid boundaries, noise, and other such difficulties. Recognition proceeds in three stages. First, candidate eyes are located by matching a simplified eye model against the responses of a robust, general purpose detector of intensity valleys and peaks. Second, the best fit of each candidate eye is found by minimizing the energy of a cost functional. Third, each candidate is accepted or rejected based on the amount of variance in the image data it explains.

Paper Details

Date Published: 1 September 1991
PDF: 13 pages
Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); doi: 10.1117/12.48426
Show Author Affiliations
Peter W. Hallinan, Harvard Univ. (United States)

Published in SPIE Proceedings Vol. 1570:
Geometric Methods in Computer Vision
Baba C. Vemuri, Editor(s)

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