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Face Recognition Using ALLE and SIFT for Human Robot Interaction

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Advances in Robotics (FIRA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5744))

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Abstract

Face recognition is a very important aspect in developing human-robot interaction (HRI) for social robots. In this paper, an efficient face recognition algorithm is introduced for building intelligent robot vision system to recognize human faces. Dimension deduction algorithms locally linear embedding (LLE) and adaptive locally linear embedding (ALLE) and feature extraction algorithm scale-invariant feature transform (SIFT) are combined to form new methods called LLE-SIFT and ALLE-SIFT for finding compact and distinctive descriptors for face images. The new feature descriptors are demonstrated to have better performance in face recognition applications than standard SIFT descriptors, which shows that the proposed method is promising for developing robot vision system of face recognition.

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Author information

Authors and Affiliations

  1. Social Robotics Lab, Interactive and Digital Medial Institute, Department of Electrical and Computer Engineering, National University of Singapore, 117576

    Yaozhang Pan, Shuzhi Sam Ge & Hongsheng He

Authors
  1. Yaozhang Pan
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  2. Shuzhi Sam Ge
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  3. Hongsheng He
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Editor information

Editors and Affiliations

  1. Dept. of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, South Korea

    Jong-Hwan Kim

  2. Social Robotics Lab, Interactive Digital Media Institute, and Edutainment Robotics Lab Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore

    Shuzhi Sam Ge

  3. National University of Singapore, Singapore

    Prahlad Vadakkepat  & Abdullah Al Manum  & 

  4. Technische Universität Dortmund, Germany

    Norbert Jesse

  5. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, P.O. Box, 117576, Singapore

    Sadasivan Puthusserypady K

  6. Institut für Informatik/I12, Technische Universität München, Boltzmannstr. 3,, D-85748, Garching b. München, Germany

    Ulrich Rückert

  7. School of Software Engineering and Data Communications, Queensland University of Technology, P.O. Box, Brisbane, Australia

    Joaquin Sitte

  8. Heinz Nixdorf Institute, University of Paderborn, P.O. Box, Paderborn, Germany

    Ulf Witkowski

  9. Interactive & Digital Media Institute, National University of Singapore, Blk E3A #02-04, 7 Engineering Drive 1, 117574, Singapore

    Ryohei Nakatsu

  10. University of Manitoba, R3T 2N2, Winnipeg, MB, Canada

    Jacky Baltes

  11. Autonomous Agents Laboratory, Department of Computer Science, University of Manitoba, P.O. Box, R3T 2N2, Winnipeg, Manitoba, Canada

    John Anderson

  12. Dept. of Education in Technology & Science, Technion - Israel Institute of Technology, 32000, Haifa, Israel

    Igor Verner

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© 2009 Springer-Verlag Berlin Heidelberg

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Pan, Y., Ge, S.S., He, H. (2009). Face Recognition Using ALLE and SIFT for Human Robot Interaction. In: Kim, JH., et al. Advances in Robotics. FIRA 2009. Lecture Notes in Computer Science, vol 5744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03983-6_9

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  • DOI: https://doi.org/10.1007/978-3-642-03983-6_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03982-9

  • Online ISBN: 978-3-642-03983-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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