Affiliation:
1. Dipartimento di Scienze dell'Informazione, Università degli Studi di Milano, Via Comelico, 39/41 - 20135 Milan, Italy
Abstract
The literature on the topic has shown a strong correlation between the degree of precision of face localization and the face recognition performance. Hence, there is a need for precise facial feature detectors, as well as objective measures for their evaluation and comparison. In this paper, we will present significant improvements to a previous method for precise eye center localization, by integrating a module for mouth localization. The technique is based on Support Vector Machines trained on optimally chosen Haar wavelet coefficients. The method has been tested on several public databases; the results are reported and compared according to a standard error measure. The tests show that the algorithm achieves high precision of localization.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Cited by
33 articles.
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