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1 September 1991 Recognizing human eyes
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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.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter W. Hallinan "Recognizing human eyes", Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991);


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