In the article were researched the principles of building systems for observation and recognition of objects. Also we have given the classification of human faces recognition methods. Authors have analized the features of operetion for the progressive calibration network (PCN) for human face recognition. And finally has been created and tested the developed face recognition algorithm as the realized software system.
- Kashkarov A.P. Systemy videonabliudenyia. Praktykum / A.P. Kashkarov. — K.: Fenyks, 2014. — 128 s.
- Damianovsky V. CCTV. Biblia videonabliudenia. Tsyfrovye i setevye tekhnolohii. Per. s anhl. / V. Damianovsky. — M.: Ai-Es-Es Press, 2006. — 480 s.
- Xuepeng Shi, Shiguang Shan, Meina Kan, Shuzhe Wu, Xilin Chen. Real-Time Rotation-Invariant Face Detection With Progressive Calibration Networks / S. Xuepeng, S. Shiguang, K. Meina, W Shuzhe, C. Xilin // Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). — 2018, pp. 2295-2303.
- Girshick R. Fast R-CNN / R. Girshick R. // The IEEE International Conference on Computer Vision (ICCV). December 2015.
- Kuzin A.V. Bazy dannykh, 5-e izdanie / Kuzin A.V., Levonysova S.V. — K.: Akademyia, 2012. — 317s.
- Skott Meiers. Effektivnoe ispolzovanie STL / M. Skott. — SPb.: Pyter, 2002. — 224 s.
- Nuruzzaman Faruqui. Open Source Computer Vision for Beginners: Learn OpenCV using C++ in fastest possible way (2nd Edition) / F. Nuruzzaman. — Kindle direct publishing, 2017.