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Localized versus Locality Preserving Representation Methods in Face Recognition Tasks

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Intelligent Systems and Technologies

Part of the book series: Studies in Computational Intelligence ((SCI,volume 217))

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Abstract

Four different localized representation methods and two manifold learning procedures are compared in terms of recognition accuracy for several face processing tasks. The techniques under investigation are: a) Non-negative Matrix Factorization (NMF); b) Local Non-negative Matrix Factorization (LNMF); c) Independent Components Analysis (ICA); d) NMF with sparse constraints (NMFsc); e) Locality Preserving Projections (Laplacianfaces); and f) Orthogonal Projection Reduction by Affinity (OPRA). A systematic comparative analysis is conducted in terms of distance metric used, number of selected features, and sources of variability on AR, Yale, and Olivetti face databases. Results indicate that the relative performance ranking of the methods is highly task dependent, and varies significantly upon the distance metric used.

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Authors and Affiliations

  1. Faculty of Electronics and Telecommunications, Technical University of Iasi, Romania, Bd. Carol I, no. 11, Iasi, 700506, Romania

    Iulian B. Ciocoiu

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  1. Iulian B. Ciocoiu
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Editors and Affiliations

  1. Universitatea Tehnica “Gheorghe Asachi” Rectorat, B-dul Prof.D.Mangeron nr. 67, 700050, Iasi, Romania

    Horia-Nicolai Teodorescu

  2. Graduate School of Information, Production and Systems (IPS), Waseda University, 2-7 Hibikino,Wakamatsuku, Kitakyushu, 808-0135, Fukuoka, Japan

    Junzo Watada

  3. Professor of Knowledge-Based Engineering, University of South Australia, 5095, Adelaide City, SA, Australia

    Lakhmi C. Jain

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Ciocoiu, I.B. (2009). Localized versus Locality Preserving Representation Methods in Face Recognition Tasks. In: Teodorescu, HN., Watada, J., Jain, L.C. (eds) Intelligent Systems and Technologies. Studies in Computational Intelligence, vol 217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01885-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-01885-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01884-8

  • Online ISBN: 978-3-642-01885-5

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