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Facial Feature Extraction Using Geometric Feature and Independent Component Analysis

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Knowledge Acquisition: Approaches, Algorithms and Applications (PKAW 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5465))

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Abstract

Automatic facial feature extraction is one of the most important and attempted problems in computer vision. It is a necessary step in face recognition, facial image compression. There are many methods have been proposed in the literature for the facial feature extraction task. However, all of them have still disadvantage such as not complete reflection about face structure, face texture. Therefore, a combination of different feature extraction methods which can integrate the complementary information should lead to improve the efficiency of feature extraction stage. In this paper we describe a methodology for improving the efficiency of feature extraction stage based on the association of two methods: geometric feature based method and Independent Component Analysis (ICA) method. Comparison of two methods of facial feature extraction: geometric feature based method combined with PCA method (called GPCA) versus geometric feature based method combined with ICA method (called GICA) on CalTech dataset has demonstrated the efficiency of GICA method. Our results show that GICA achieved good performance 96.57% compared to 94.70% of GPCA method. Furthermore, we compare two methods mentioned above on our dataset, with performance of GICA being 98.94% better 96.78% of GPCA method. The experiment results have confirmed the benefits of the association geometric feature based method and ICA method in facial feature extraction.

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Author information

Authors and Affiliations

  1. Department of Computer Sciences, University of Natural Sciences, HCMC, Vietnam

    Toan Thanh Do & Thai Hoang Le

Authors
  1. Toan Thanh Do
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  2. Thai Hoang Le
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Editors and Affiliations

  1. Computing Department, Division of Information and Communication Sciences, Macquarie University, NSW, 2109, Sydney, Australia

    Debbie Richards

  2. School of Computing ad Information Systems, University of Tasmania , Launceton, TAS 7250, Tasmania, Australia

    Byeong-Ho Kang

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© 2009 Springer-Verlag Berlin Heidelberg

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Thanh Do, T., Hoang Le, T. (2009). Facial Feature Extraction Using Geometric Feature and Independent Component Analysis. In: Richards, D., Kang, BH. (eds) Knowledge Acquisition: Approaches, Algorithms and Applications. PKAW 2008. Lecture Notes in Computer Science(), vol 5465. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01715-5_20

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  • DOI: https://doi.org/10.1007/978-3-642-01715-5_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01714-8

  • Online ISBN: 978-3-642-01715-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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