In this paper, we present a face location system in a complex background and robust to a wide range of lighting conditions, likely to appear in an indoor environment. The complete system contains two parts: the face locator and the face tracker. We will only describe the face locator. Face hypothesis are obtained combining a pyramidal greylevel template matching and a geometrical measure based on the facial feature organization. Classification to face or non-face is realized by linear discriminant analysis (LDA) on the principal components analysis (PCA) of a 26-dimensional feature vector extracted from the face hypothesis. Experiments on 1500 images in a cluttered background with 12 lighting conditions are very encouraging. © Springer-Verlag 2001.
CITATION STYLE
Mariani, R. (2001). A face location algorithm robust to complex lighting conditions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2091 LNCS, pp. 115–120). Springer Verlag. https://doi.org/10.1007/3-540-45344-x_18
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