Automation of people’s faces recognition by photograph
Problemy fiziki, matematiki i tehniki, no. 3 (2017), pp. 91-95.

Voir la notice de l'article provenant de la source Math-Net.Ru

An algorithm for faces recognition is described. The algorithm has two stages. The aim of the first stage is to detect faces on source images; the aim of the second stage is to create attributes describing detected faces. Those attributes are used to compare faces and decide whether there is the same or different person on different images.
Keywords: face recognition, Viola–Jones method, principal component analysis.
@article{PFMT_2017_3_a15,
     author = {I. V. Tsimokhin and N. B. Osipenko},
     title = {Automation of people{\textquoteright}s faces recognition by photograph},
     journal = {Problemy fiziki, matematiki i tehniki},
     pages = {91--95},
     publisher = {mathdoc},
     number = {3},
     year = {2017},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/PFMT_2017_3_a15/}
}
TY  - JOUR
AU  - I. V. Tsimokhin
AU  - N. B. Osipenko
TI  - Automation of people’s faces recognition by photograph
JO  - Problemy fiziki, matematiki i tehniki
PY  - 2017
SP  - 91
EP  - 95
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/PFMT_2017_3_a15/
LA  - ru
ID  - PFMT_2017_3_a15
ER  - 
%0 Journal Article
%A I. V. Tsimokhin
%A N. B. Osipenko
%T Automation of people’s faces recognition by photograph
%J Problemy fiziki, matematiki i tehniki
%D 2017
%P 91-95
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/PFMT_2017_3_a15/
%G ru
%F PFMT_2017_3_a15
I. V. Tsimokhin; N. B. Osipenko. Automation of people’s faces recognition by photograph. Problemy fiziki, matematiki i tehniki, no. 3 (2017), pp. 91-95. http://geodesic.mathdoc.fr/item/PFMT_2017_3_a15/

[1] P. Viola, M. Jones, International Journal of Computer Vision, 2001, no. 4, 34–47

[2] R. Lienhart, J. Maydt, “An Extended Set of Haar-like Features for Rapid Object Detection”, ICIP02, 2002, 900–903

[3] M. A. Turk, A. P. Pentland, “Face recognition using eigenfaces”, Computer Vision and Pattern Recognition, 1991, 586–591

[4] K. Delac, M. Grgic, P. Liatsis, “Apperance-based Statistical Methods for Face Recognition”, Proceedings of the 47th International Symposium ELMAR-2005 focused on Multimedia Systems and Applications (Zagreb, 2005), 151–158

[5] OpenCV Library, (Date of access: 01.05.2017) http://opencv.org/

[6] Georgia Tech face database, (Date of access: 10.03.2017) http://www.anefian.com/research/face_reco.htm

[7] Pexels. Free stock photos, (Date of access: 01.05.2017) https://www.pexels.com

[8] S. A. Aivazyan, V. M. Bukhshtaber, I. S. Enyukov, Prikladnaya statistika: Klassifikatsiya i snizhenie razmernosti, Spravochnoe izdanie, Finansy i statistika, M., 1989, 605 pp.

[9] Numpy and Scipy Documentation, (Date of access: 01.05.2017) https://docs.scipy.org/doc/