Increasing the Training Set in Face Recognition Tasks by Using a 3D Model of a Face | Zendy

Olga Krutikova | Zendy; Aleksandrs Glazs | Zendy

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Increasing the Training Set in Face Recognition Tasks by Using a 3D Model of a Face

Author(s) -

Olga Krutikova,

Aleksandrs Glazs

Publication year - 2015

Publication title -

technologies of computer control

Language(s) - English

Resource type - Journals

eISSN - 2256-0343

pISSN - 2256-0351

DOI - 10.7250/tcc.2014.002

Subject(s) - face (sociological concept) , facial recognition system , computer science , set (abstract data type) , artificial intelligence , training set , computer vision , head (geology) , base (topology) , training (meteorology) , pattern recognition (psychology) , data set , mathematics , geography , mathematical analysis , social science , geomorphology , sociology , meteorology , programming language , geology

The paper proposes a method for face recognition, which uses a 3D model of the head, which is turned at different angles to extend the size of the training set. Control points are placed on the images, which have been created using the 3D model of the head, and the distance ratios between the control points are stored in the database. Face recognition algorithm would look for two images of faces in the data base which have minimal difference between the turn angles of the head and the distance ratios.

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