Kernel-based regularized neighbourhood preserving embedding in face recognition

Pang Ying Han, Andrew Teoh Beng Jin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Face images always have significant intra-class variations due to different poses, illuminations and facial expressions. These variations trigger substantial deviation from the linearity assumption of data structure, which is essential in formulating linear dimension reduction technique. In this paper, we present a kernel based regularized graph embedding dimension reduction technique, known as kernel-based Regularized Neighbourhood Preserving Embedding (KRNPE) to address this problem. KRNPE first exploits kernel function to unfold the nonlinear intrinsic facial data structure. Neighbourhood Preserving Embedding, a graph embedding based linear dimension reduction technique, is then regulated based on Adaptive Locality Preserving Regulation Model, established in [7] to enhance the locality preserving capability of the projection features, leading to better discriminating capability and generalization performance. Experimental results on PIE and FERET face databases validate the effectiveness of KRNPE.

Original languageEnglish
Title of host publicationProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
Pages883-888
Number of pages6
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 - Singapore, Singapore
Duration: 2012 Jul 182012 Jul 20

Publication series

NameProceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

Other

Other2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012
CountrySingapore
CitySingapore
Period12/7/1812/7/20

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Han, P. Y., & Jin, A. T. B. (2012). Kernel-based regularized neighbourhood preserving embedding in face recognition. In Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012 (pp. 883-888). [6360849] (Proceedings of the 2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012). https://doi.org/10.1109/ICIEA.2012.6360849