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A unified framework for improving the accuracy of all holistic face identification algorithms

Electoral College for human face identification by computing machinery

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Abstract

Reconstructing the challenging human face identification process as a stability problem, we show that Electoral College can be used as a framework that provides a significantly enhanced face identification process by improving the accuracy of all holistic algorithms. The results are demonstrated by extensive experiments on benchmark face databases applying the Electoral College framework embedded with standard baseline and newly developed face identification algorithms.

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Authors and Affiliations

  1. Computer Science Department, University of Northern British Columbia, Prince George, BC, V2N 4Z9, Canada

    Liang Chen

  2. R & D Center, SunFlare Company, Shinjuku Hirose Bldg, Yotsuya 4-7, Shinjuku-ku, Tokyo, 160-0004, Japan

    Naoyuki Tokuda

Authors
  1. Liang Chen
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  2. Naoyuki Tokuda
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Correspondence to Liang Chen.

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Chen, L., Tokuda, N. A unified framework for improving the accuracy of all holistic face identification algorithms. Artif Intell Rev 33, 107–122 (2010). https://doi.org/10.1007/s10462-009-9139-0

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  • DOI: https://doi.org/10.1007/s10462-009-9139-0

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