Face Recognition Using Local Variation

Abstract:

In this paper, a novel approach, namely local variation projection (LVP), is presented for face recognition. LVP defines an adjacency graph to model the variation among nearby face images, which includes the within-class variation and between-class variation, also called margin. In order to better detect the discriminant structure, we assign a small weight to the variation among nearby face images from the same class. Based on this content, a concise feature extraction criterion is built for dimensionality reduction. Experiments indicate the effectiveness of our proposed approach.

• Periodical: Applied Mechanics and Materials (Volumes 236-237)
• Pages: 875-880
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.236-237.875
• Online since: November 2012
• Authors: Jing Jing Liu, Wei Guo Shen, Quan Xue Gao, Xiu Juan Hao
• Keywords: Dimensionality Reduction, Face Recognition, Manifold Learning, Variation

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