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

Authors:
Liang Chen;Naoyuki Tokuda
Affiliations:
Computer Science Department, University of Northern British Columbia, Prince George, Canada V2N 4Z9;R & D Center, SunFlare Company, Shinjuku-ku, Tokyo, Japan 160-0004
Venue:
Artificial Intelligence Review
Year:
2010

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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.