Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/41395
Title: Discriminative scale invariant feature transform (SIFT FLD) model for efficient representation and accurate recognition of faces
Authors: Shekar, B.H.
Thippeswamy, G.
Shivakumara, P. 
Keywords: Eigenfaces
Face recognition
Fisherfaces
Linear discriminant analysis
Local descriptors
Issue Date: 2009
Source: Shekar, B.H.,Thippeswamy, G.,Shivakumara, P. (2009). Discriminative scale invariant feature transform (SIFT FLD) model for efficient representation and accurate recognition of faces. Proceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009 : 1914-1927. ScholarBank@NUS Repository.
Abstract: In this paper, we propose a new discriminative scale invariant feature transform (SIFTFLD) model for efficient representation and accurate recognition of faces. Discriminative SIFT descriptors are extracted for compact representation of faces. Unlike PCA-SIFT that employs PCA on normalized gradient patch; we employ FLD on smoothed weighted histograms. The proposed model has better recognition performance in an unstructured environment and invariant to in-plane rotations. To establish the superiority of the proposed model, we have experimentally compared the performance of our new algorithm with recently proposed (2D)2-FLD on the benchmark databases: AT&T and CALTECH face datasets. Copyright © 2009 by IICAI.
Source Title: Proceedings of the 4th Indian International Conference on Artificial Intelligence, IICAI 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/41395
ISBN: 9780972741279
Appears in Collections:Staff Publications

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