Simile Classifiers for Face Classification

ЗаголовокSimile Classifiers for Face Classification
Тип публикацииConference Paper
Год публикации2012
АвторыKonushin V, Lukina T, Kuharenko A, Konushin A
Refereed DesignationRefereed
КонференцияGraphiCon
Страницы108-112
Язык публикацииEnglish
Ключевые словаattribute classification, classifier training, gender classification
Аннотация

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.

URLhttp://www.graphicon.ru/proceedings/2012/conference/RU1%20-%20Biometry/gc2012konushin.pdf
Ключ цитирования1000