Using object-oriented databases in face recognition
https://doi.org/10.21122/2309-4923-2020-2-54-60
Abstract
The aim of the work is to develop an algorithm functioning by a face recognition system using object-oriented databases. The system provides automatic identification of the desired object or identifies someone using a digital photo or video frame from a video source. The technology includes comparing pre-scanned face elements from the resulting image with prototypes of faces stored in the database. Modern packages of object-oriented databases give the user the opportunity to create a new class with the specified attributes and methods, obtain classes that inherit attributes and methods from super classes, create instances of the class, each of which has a unique object identifier, extract these instances one by one or in groups, and also download and perform these procedures. Using a convolutional neural network in the algorithm allows the transition from specific features of the image to more abstract details.
About the Authors
X. C. Dong
Belarusian State University of Informatics and Radioelectronics
Belarus
Dong Xuan Chinh – graduate student at the Department of Information and Computer Systems Design
Belarus
Dong Xuan Chinh – graduate student at the Department of Information and Computer Systems Design
V. I. Ionin
Belarusian State University of Informatics and Radioelectronics
Belarus
Ionin Victor Sergeevich – candidate of Technical Sciences, Associate Professor of the Department of Designing Information and Computer Systems
Belarus
Ionin Victor Sergeevich – candidate of Technical Sciences, Associate Professor of the Department of Designing Information and Computer Systems
References
1. Анализ существующих подходов к распознаванию лиц. – [Электронный ресурс]. – Код доступа: http://paclub.ru/assets/curriculum/programs. – Дата доступа 14.01.2020.
2. Объектно-ориентированные базы данных – основные концепции, организация и управление: краткий обзор. – [Электронный ресурс]. – Код доступа: http://citforum.ru/database/articles/art_24.shtml. – Дата доступа 14.01.2020.
3. Serge Abiteboul. Towards a Deductive Object-Oriented Database Language // Data and Knowledge Eng. – 5. – 1990. – 263–287.
4. Kyuchul Lee, Sukho Lee. An Object-Oriented Approach to Data/Knowledge Modelling Based on Logic // 6th Int. Conf. Data Eng., Los Angeles, Calif., USA, Febr. 5–9, 1990. – 289–294.
5. A. M. Alashqur, S. Y. W. Su, H. Lam. A Rule-based Language for Deductive Object-Oriented Databases // 6th Int. Conf. Data Eng., Los Angeles, Calif., USA, Febr. 5–9, 1990. – 58–67.
6. Lois M. L. Delcambre, Karen C. Davis. Automatic Validation of Object-Oriented Database Structures // 5th Int. Conf. Data Eng., Los Angeles, Calif., USA, Febr. 6–10, 1989. – 2–9.
7. Introducing Convolutional Neural Networks in Deep Learning. – [Электронный ресурс]. – Код доступа: https:// towardsdatascience.com/introducing-convolutional-neural-networks-in-deep-learning-400f9c3ad5e9. – Дата доступа 18.01.2020.
8. Labeled Faces in the Wild. – [Электронный ресурс]. – Код доступа: http://vis-www.cs.umass.edu/lfw/. – Дата доступа 18.01.2020.
9. A Detailed Guide to 7 Loss Functions for Machine Learning Algorithms with Python Code. – [Электронный ресурс]. – Код доступа: https://www.analyticsvidhya.com/blog/2019/08/detailed-guide-7-loss-functions-machine-learning-python-code/. – Дата доступа 18.01.2020.
10. Definition and Overview of ODBMS. – [Электронный ресурс]. – Код доступа: https://www.geeksforgeeks.org/definition-and-overview-of-odbms. – Дата доступа 18.01.2020.
Review
For citations:
Dong X.C., Ionin V.I. Using object-oriented databases in face recognition. «System analysis and applied information science». 2020;(2):54-60. (In Russ.) https://doi.org/10.21122/2309-4923-2020-2-54-60
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