[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.33851/JMIS.2019.6.1.15

Analogical Face Generation based on Feature Points

Yoon, Andy Kyung-yong (Special School of University of San Martin)
Park, Ki-cheul (Neosecu Co., Ltd.)
Oh, Duck-kyo (Neosecu Co., Ltd.)
Cho, Hye-young (Neosecu Co., Ltd.)
Jang, Jung-hyuk (Neosecu Co., Ltd.)

Publication Information

Journal of Multimedia Information System / v.6, no.1, 2019 , pp. 15-22 More about this Journal

Abstract

There are many ways to perform face recognition. The first step of face recognition is the face detection step. If the face is not found in the first step, the face recognition fails. Face detection research has many difficulties because it can be varied according to face size change, left and right rotation and up and down rotation, side face and front face, facial expression, and light condition. In this study, facial features are extracted and the extracted features are geometrically reconstructed in order to improve face recognition rate in extracted face region. Also, it is aimed to adjust face angle using reconstructed facial feature vector, and to improve recognition rate for each face angle. In the recognition attempt using the result after the geometric reconstruction, both the up and down and the left and right facial angles have improved recognition performance.

Keywords

Face Recognition; Face Detection; Feature Vector; kNN; Blend Shape; 3D Face Generation; Face Depth Calculation;

Citations & Related Records

Times Cited By KSCI : 1 (Citation Analysis)

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