Self organizing maps for 3D face understanding

Auteurs

J. T. Starczewski, S. Pabiasz, N. Vladymyrska, A. Marvuglia, C. Napoli, and M. Woźniak

Référence

in Artificial Intelligence and Soft Computing: 15th International Conference, ICAISC 2016, Zakopane, Poland, June 12-16, 2016, Proceedings, Part II. L. Rutkowski, M. Korytkowski, R. Scherer, R. Tadeusiewicz, A. L. Zadeh, and M. J. Zurada (Eds.), Lecture Notes in Computer Science, vol. 9693, Springer, pp. 210-217, 2016

Description

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.

Lien

doi: 10.1007/978-3-319-39384-1_19