Simile Classifiers for Face Classification
نویسندگان
چکیده
We present a new approach to face classification using simile classifiers. Unlike other methods we explicitly estimate similarity distances to the known reference people and use these similarities as high-level features for the classification of the test face. We test our algorithm on gender classification problem. Our algorithm shows classification accuracy of 92.96% on LFW dataset.
منابع مشابه
Attribute and Simile Classifiers for Face Verification (In submission please do not distribute.)
We present two novel methods for face verification. Our first method – “attribute” classifiers – uses binary classifiers trained to recognize the presence or absence of describable aspects of visual appearance (e.g., gender, race, and age). Our second method – “simile” classifiers – removes the manual labeling required for attribute classification and instead learns the similarity of faces, or ...
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