Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-03983-6_9
Title: Face recognition using ALLE and SIFT for human robot interaction
Authors: Pan, Y.
Ge, S.S. 
He, H.
Issue Date: 2009
Citation: Pan, Y.,Ge, S.S.,He, H. (2009). Face recognition using ALLE and SIFT for human robot interaction. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5744 LNCS : 53-62. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-03983-6_9
Abstract: Face recognition is a very important aspect in developing human-robot interaction (HRI) for social robots. In this paper, an efficient face recognition algorithm is introduced for building intelligent robot vision system to recognize human faces. Dimension deduction algorithms locally linear embedding (LLE) and adaptive locally linear embedding (ALLE) and feature extraction algorithm scale-invariant feature transform (SIFT) are combined to form new methods called LLE-SIFT and ALLE-SIFT for finding compact and distinctive descriptors for face images. The new feature descriptors are demonstrated to have better performance in face recognition applications than standard SIFT descriptors, which shows that the proposed method is promising for developing robot vision system of face recognition. © 2009 Springer.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/70287
ISBN: 3642039820
ISSN: 03029743
DOI: 10.1007/978-3-642-03983-6_9
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