Abstract
We present in this paper a new facial feature localizer. It uses a kind of auto-associative neural network trained to localize specific facial features (like eyes and mouth corners) in orientation-free faces. One possible extension is presented where several specialized detectors are trained to deal with each face orientation. To select the best localization hypothesis, we combine radiometric and probabilistic information. The method is quite fast and accurate. The mean localization error (estimated on more than 700 test images) is lower than 9%.
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Prevost, L., Belaroussi, R., Milgram, M. (2006). Multiple Neural Networks for Facial Feature Localization in Orientation-Free Face Images. In: Schwenker, F., Marinai, S. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2006. Lecture Notes in Computer Science(), vol 4087. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11829898_17
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DOI: https://doi.org/10.1007/11829898_17
Publisher Name: Springer, Berlin, Heidelberg
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