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New perspectives in face correlation research: a tutorial
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DOI：10.1364/AOP.9.000001.png)
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Abstract
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In recent years, correlation-filter (CF)-based face recognition algorithms have attracted increasing interest in the field of pattern recognition and have achieved impressive results in discrimination, efficiency, location accuracy, and robustness. In this tutorial paper, our goal is to help the reader get a broad overview of CFs in three respects: design, implementation, and application. We review typical face recognition algorithms with implications for the design of CFs. We discuss and compare the numerical and optical implementations of correlators. Some newly proposed implementation schemes and application examples are also presented to verify the feasibility and effectiveness of CFs as a powerful recognition tool. (C) 2017 Optical Society of America
Keywords:
INDEPENDENT COMPONENT ANALYSIS
QUADRATIC CORRELATION FILTERS
OPTICAL-PATTERN RECOGNITION
DEPENDENCE FEATURE ANALYSIS
JOINT TRANSFORM CORRELATOR
VISUAL TRACKING
AVERAGE
ILLUMINATION
SYSTEM
ROBUST
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