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Face Recognition Using Foveal Vision

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Biologically Motivated Computer Vision (BMCV 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1811))

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Abstract

Data from human subjects recorded by an eyetracker while they are learning new faces shows a high degree of similarity in saccadic eye movements over a face. Such experiments suggest face recognition can be modeled as a sequential process, with each fixation providing observations using both foveal and parafoveal information. We describe a sequential model of face recognition that is incremental and scalable to large face images. Two approaches to implementing an artificial fovea are described, which transform a constant resolution image into a variable resolution image with acute resolution in the fovea, and an exponential decrease in resolution towards the periphery. For each individual in a database of faces, a hidden-Markov model (HMM) classifier is learned, where the observation sequences necessary to learn the HMMs are generated by fixating on different regions of a face. Detailed experimental results are provided which show the two foveal HMM classifiers outperform a more traditional HMM classifier built by moving a horizontal window from top to bottom on a highly subsampled face image.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Michigan State University, USA

    Silviu Minut & Sridhar Mahadevan

  2. Department of Psychology, Michigan State University, USA

    John M. Henderson

  3. Department of Zoology, Michigan State University, East Lansing, MI, 48823

    Fred C. Dyer

Authors
  1. Silviu Minut
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  2. Sridhar Mahadevan
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  3. John M. Henderson
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  4. Fred C. Dyer
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Editor information

Editors and Affiliations

  1. Center for Artificial Vision Research, Korea University, Anam-dong, Seongbuk-ku, Seoul, 136-701, Korea

    Seong-Whan Lee

  2. Max-Planck-Institute for Biological Cybernetics, Spemannstr. 38, 72076, Tübingen, Germany

    Heinrich H. Bülthoff

  3. Department of Brain and Cognitive Sciences Artificial Intelligence Laboratory, E25-218, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA, 02142, USA

    Tomaso Poggio

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© 2000 Springer-Verlag Berlin Heidelberg

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Minut, S., Mahadevan, S., Henderson, J.M., Dyer, F.C. (2000). Face Recognition Using Foveal Vision. In: Lee, SW., Bülthoff, H.H., Poggio, T. (eds) Biologically Motivated Computer Vision. BMCV 2000. Lecture Notes in Computer Science, vol 1811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45482-9_43

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  • DOI: https://doi.org/10.1007/3-540-45482-9_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67560-0

  • Online ISBN: 978-3-540-45482-3

  • eBook Packages: Springer Book Archive

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