Landmarks are unique points that can be located on every face. Facial landmarks typically recognized by people are correlated with anthropomorphic points. Our purpose is to employ in 3D face recognition such landmarks that are easy to interpret. Face understanding is construed as identification of face characteristic points with automatic labeling of them. In this paper, we apply methods based on Self Organizing Maps to understand 3D faces.

Self Organizing Maps for 3D Face Understanding

NAPOLI, CHRISTIAN;
2016-01-01

Abstract

Landmarks are unique points that can be located on every face. Facial landmarks typically recognized by people are correlated with anthropomorphic points. Our purpose is to employ in 3D face recognition such landmarks that are easy to interpret. Face understanding is construed as identification of face characteristic points with automatic labeling of them. In this paper, we apply methods based on Self Organizing Maps to understand 3D faces.
2016
978-331939383-4
Artificial intelligence; Image processing; Self organizing maps
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/249524
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