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Face Recognition Dimensionality Reduction Based on LLE and ISOMAP

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Informatics and Management Science V

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 208))

Abstract

Local linear embedding (LLE) and isometric feature mapping (ISOMAP) are two basic patterns of nonlinear dimensionality reduction. Their respective strengths and weaknesses in face recognition deserve deep-going comparative study. Therefore, this paper is to test the two patterns’ performance efficiency in different parameters, analyze and summarize the two dimensionality reduction pattern’s characteristics and scope of application, apply LLE and main constituent analysis into face recognition and summarize probability of detection of face recognition.

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References

  1. Zejie W (2008) Comparative analysis of two types of nonlinear reduced-dimensional manifold learning algorithm. Academic paper of Shanghai University of Engineering Science 22(1):54–59

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  2. Ziqiang W, Xu Q, Min K (2008) A summary of manifold learning algorithm. Comput Eng Appl 44(35):9–12

    Google Scholar 

  3. Qing L (2008) Semi-supervised handwriting recognition. Chinese Science and Technology University, 49:372–378

    Google Scholar 

  4. Varini C, Degenhard A, Nattkemper TW (2006) ISOLLE: LLE with geodesic distance. Neurocomputing 17:1768–1771

    Article  Google Scholar 

  5. Roweis ST, Saul LK (2000) Nonlinear dimensionality reduction by locally linear embedding. Science 8:2323–2326

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Computer and Communication, Hunan University of Technology, Zhuzhou, Hunan, 412007, China

    Tao Zhang & Lixin Tao

  2. Hunan City University, Yiyang, 413000, China

    Shu Li

  3. Modern Education Technology Center, Hunan University of Technology, Zhuzhou, Hunan, 412007, China

    Shuguang Wu

Authors
  1. Tao Zhang
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  2. Shu Li
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  3. Shuguang Wu
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  4. Lixin Tao
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Corresponding author

Correspondence to Shu Li .

Editor information

Editors and Affiliations

  1. , College of Elementary Education, Chongqing Normal University, Chongqing, 400700, China, People's Republic

    Wenjiang Du

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© 2013 Springer-Verlag London

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Cite this paper

Zhang, T., Li, S., Wu, S., Tao, L. (2013). Face Recognition Dimensionality Reduction Based on LLE and ISOMAP. In: Du, W. (eds) Informatics and Management Science V. Lecture Notes in Electrical Engineering, vol 208. Springer, London. https://doi.org/10.1007/978-1-4471-4796-1_99

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  • DOI: https://doi.org/10.1007/978-1-4471-4796-1_99

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4795-4

  • Online ISBN: 978-1-4471-4796-1

  • eBook Packages: EngineeringEngineering (R0)

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