Development of an intelligent system for face recognition based on neural networks
Abstract
Personal identification systems are widely used in everyday life. There are many methods for extracting faces in the original image, the most perspective of which is the usage of algorithms based on neural networks. The aim of the study was to design and test an intelligent system for face recognition based on this technology. In the course of a preliminary analysis of machine learning methods for solving the problem, it was found that it is most appropriate to use machine learning methods based on the analysis of facial micromotions with the subsequent construction of a map of points. Based on the data obtained, the development of a face identification system using computer vision technology was carried out, which was based on the method of creating complex architectures using various features with additional algorithms. A distinctive feature of the developed intelligent system is the ability to analyze several frames that confirm micromovements of the head or blinking. As a result of testing the resulting system using the algorithm of gradient boosting of regression trees, a map of 68 face points was obtained, on the basis of which human faces were identified with objects from the database.
Full Text:
PDF (Russian)References
Vanzha T.V. Statistical analysis of modern methods of recognition of faces and emotions // Informatics and Cybernetics. - № 2 (16). - 2019.- P. 64-70. - https://elibrary.ru/item.asp?id=41142230.
Leontiev A.V. Russian software and hardware solution for recognizing the emotional state of people for intelligent ecosystems. A.V. Leontiev, A.V. Shershakov, E.S. Yanakova // Nanoindustry. - S96-1. - 2020 .- P. 125-128. - https://elibrary.ru/item.asp?id=43004721.
Grechany S.A. Face recognition in modern video surveillance systems using the example of TM equipment / S.А. Grechany, N.Yu. Fedina, M.V. Khramykov // Security, security, communication. № 5-1. - 2020. - P. 63-68. - https://www.elibrary.ru/item.asp?id=43050522&.
Ostanina E.A. On some aspects of face recognition technology // Human capital. - № 5 (137). - 2020 .- P. 142-152. - https://elibrary.ru/item.asp?id=42661637.
Tagirov T.R. System of registration of control of visiting premises // Youth Bulletin of the Ufa State Aviation Technical University. - № 2 (23). - 2020 .- P. 124-126. - https://elibrary.ru/item.asp?id=42965587.
Katys P.G. Image processing in face recognition systems // Modern science: actual problems of theory and practice. Series: natural and technical sciences. - №. 1. - 2020 .- P. 92-95. - https://elibrary.ru/item.asp?id=42632331.
Kryazhev A.S. Study of the possibilities of implementing the face recognition module for access control and management systems. Materials of the IV International Scientific and Practical Conference of Students, Postgraduates and Young Scientists "Fundamental and Applied Research of Young Scientists". - 2020 .- P. 356-360. - https://elibrary.ru/item.asp?id=42731597.
Rodishev D.D. Use of technologies for identification of a person by face to record visits to educational institutions. - Materials of the 27th Regional Scientific Student Conference "Intellectual potential of Siberia". - 2019.- P. 69-70. - https://elibrary.ru/item.asp?id=41410656.
Ersultanova Z.P. Intellectual information system in education. - Materials of the VIII International Scientific and Practical Conference "Modern Trends in Natural and Mathematical Education: School - University". - 2019. - P. 49-52. - https://elibrary.ru/item.asp?id=37273922.
Rudeshko N.A. Intelligent face recognition system for schoolchildren / N.А. Rudeshko, Yu.V. Dubenko. - Materials of the VIII All-Russian Scientific Conference of Young Scientists, Postgraduates and Students "Problems of Automation. regional administration. communication and automation (Sails-2019) ". - 2019 .- P. 271-276. - https://elibrary.ru/item.asp?id=41879198.
Aytbenova A.A. Intellectual information system in education / A.A. Aitbenova, G.B. Dauletbaeva // Mathematical and software systems in industrial and social spheres. - № 1. - 2019. - P. 30-35. - https://elibrary.ru/item.asp?id=41602667.
Filippenko V.A. Review of methods of face recognition in a video stream. Collection of scientific articles of the 4th international scientific conference of promising developments of young scientists "Science of the young - the future of Russia." - 2019 .- P. 188-191. - https://elibrary.ru/item.asp?id=41703985.
Ryumin D.A. Automatic face detection for human-machine interaction. D.A. Ryumin, A.A. Aksenov, A.A. Karpov. Materials of the XLVIII scientific and educational-methodical conference of ITMO University. - 2019. - P. 33-37. - https://elibrary.ru/item.asp?id=42151824.
Katin O.I. Research of ways to improve the performance of the face recognition system / O.I. Katin, K.I. Goryanin, D.Yu. Donskoy // Scientific Review. pedagogical sciences. - № 3-3. - 2019 .- P. 45-47. - https://elibrary.ru/item.asp?id=38506301.
Barashko E.N. New systems of search and face recognition / E.N. Barashko, K.D. Kruzhilin // Society. - № 2 (13). - 2019 .- P. 21-23. - https://elibrary.ru/item.asp?id=39131066.
Wai Yang Ming. Application of statistical data processing to improve the efficiency of face recognition using the method of principal components / Wai Yang Ming, Yu.P. Lisovets, Thet Naing Vin // Electronic Information Systems. - № 2 (21). - 2019 .- P. 33-42. - https://elibrary.ru/item.asp?id=38566109.
Martins P. Gradient Shape Model / P. Martins, J.F. Henriques, J. Batista // Int J Comput Vis 128, 2828-2848 (2020). https://doi.org/10.1007/s11263-020-01341-y.
Cevikalp H. Video Based Face Recognition by Using Discriminatively Learned Convex Models / H. Cevikalp, G.G. Dordinejad // Int J Comput Vis 128, 3000-3014 (2020). https://doi.org/10.1007/s11263-020-01356-5.
Nakane T. Application of evolutionary and swarm optimization in computer vision: a literature survey / T. Nakane, N. Bold, H. Sun // IPSJ T Comput Vis Appl 12, 3 (2020). https://doi.org/10.1186/s41074-020-00065-9.
Refbacks
- There are currently no refbacks.
Abava Кибербезопасность MoNeTec 2024
ISSN: 2307-8162