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Author Fabry, T. ♦ Vandermeulen, D. ♦ Suetens, P.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2008
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods ♦ Natural sciences & mathematics ♦ Life sciences; biology ♦ Biochemistry
Subject Keyword Image recognition ♦ Shape ♦ Image databases ♦ Iterative closest point algorithm ♦ Face recognition ♦ Clouds ♦ Humans ♦ Robustness ♦ Face detection ♦ Kernel
Abstract 3D face recognition is a widely researched problem for wich many methods have been proposed. Unfortunately, most of these methods need vast prior knowledge in the form of large 3D face training sets. Also, many methods need point correspondences, which are hard to obtain. In this paper, we present a general 3D face recognition method based on point cloud kernel correlation and kernel density estimation for registration, which doesn't make use of a training set of faces or point correspondences and can handle noisy, unpreprocessed face scans. Initial experiments on the publicly available SHREC 2008 3D face database show good face recognition accuracy and robust behavior across face expressions.
Description Author affiliation: Dept. of Electr. Eng., Katholieke Univ. Leuven, Leuven (Fabry, T.; Vandermeulen, D.; Suetens, P.)
ISBN 9781424427291
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-09-29
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 7.22 MB
Page Count 6
Starting Page 1
Ending Page 6

Source: IEEE Xplore Digital Library