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Cluster Analysis of Facial Video Data in Video Surveillance Systems Using Deep Learning
P. 113–120.
Savchenko A., Sokolova Anastasiia D.
In this paper, we propose the approach of structuring information in video surveillance systems by grouping the videos, which contain identical faces. First, the faces are detected in each frame and features of each facial region are extracted at the output of preliminarily trained deep convolution neural networks. Second, the tracks that contain identical faces are grouped using face verification algorithms and hierarchical agglomerative clustering. In the experimental study with the YTF dataset, we examined several ways to aggregate features of individual frame in order to obtain descriptor of the whole video track. It was demonstrated that the most accurate and fast algorithm is the matching of normalized average feature vectors.
In book
Valery A. Kalyagin, Panos M. Pardalos, Oleg Prokopyev, Irina Utkina Vol. 247. , Springer, 2018.
Lebedev O. B., Черкасов Р. И., Известия ЮФУ. Технические науки 2025 № 5(247) С. 254–276
This paper considers the application of artificial intelligence technologies, in particular computer vision, in visual information processing systems. A comprehensive analysis of neural network approaches to solving computer vision problems is carried out, including systematization of key types of problems: image classification, object detection and semantic segmentation. The architectural principles of convolutional neural networks are ...
Added: September 10, 2026
Starodubov K., Гвасалия Г. В., Карасев П. И., Нано-био-технологии. Тепло- и электроэнергетика. Математическое моделирование: сборник статей III международной научно-практической конференции (Липецкий государственный технический университет, Липецк, Россия) 2025 С. 219–223
This paper discusses the concept of neural networks, convolutional neural networks, their architecture and their operation principle. The main attention is paid to testing the reliability of storing images of people as embeddings, which are considered to be unrecoverable in the original image. In the course of the research an experiment is carried out: the ...
Added: September 6, 2026
Shadrina E. V., Мохова В. О., Загоскин В. А. et al., Нижегородский психологический альманах 2024 № 2
The article considers the problem of learning of recognizing emotions from pictures. A review and analysis of domestic and foreign works of scientists dealing with the problem of emotional intelligence was carried out. Its formation, influence on human activity and existing variants of its structure were considered, and common features in the understanding of emotional ...
Added: April 9, 2026
Pikul A. S., В кн.: Альманах научных работ молодых ученых университета ИТМО. Материалы Пятьдесят третьей (LIII) научной и учебно-методической конференции Том 1.: СПб.: Университет ИТМО, 2024. С. 338–342.
Предложен новый подход для улучшения распознавания атак презентации на биометрическую систему распознавания лиц с помощью сверточной сети с механизмом внимания. Проверена центральная гипотеза, которая заключалась в том, что с помощью механизма внимания возможно улучшить результаты работы исходной сверточной нейронной сети. В ходе экспериментов гипотеза была подтверждена. Наибольший прирост по качеству был достигнут на наборе данных ...
Added: December 13, 2025
Pikul A. S., Лепендин А. А., Труды молодых ученых Алтайского государственного университета 2023 № 20 С. 190–193
Представлен новый подход для выявления атак презентации на системы распознавания по лицу. Он основан на использовании механизма графового внимания, применяемого к промежуточным картам характеристик изображений лица, вычисленным сверточной сетью ResNet18. Показано, что предложенный подход позволил добиться высокого качества распознавания поддельных изображений при лицевой биометрической верификации, сравнимого с имеющимися в настоящее время альтернативными решениями. ...
Added: December 12, 2025
Pikul A. S., Безопасность информационных технологий 2024 Т. 31 № 4 С. 116–127
This article explores the potential use of modern computer vision architectures for the task of deepfake detection. The following architectures are considered: EfficientNet, Vision Transformer (ViT), VisionLSTM (ViL), Vision KAN, and Mamba Vision. The novelty of the approach lies in the application and comparison of these architectures, as well as their combination into paired ensembles ...
Added: December 12, 2025
Sanina A., Сафронова Ю. А., Ataeva A., Информационное общество 2025 № 4 С. 138–146
The article analyzes the relationship between the presence of video surveillance systems (in courtyards, entrances and crowded places) and crime rates in Moscow within the framework of the concept of “Crime Prevention through Environmental Design” (CPTED). The results show that the high density of CCTV cameras does not guarantee a reduction in the crime rate, ...
Added: September 1, 2025
Morozov D., Garipov T., Lyashevskaya O. et al., Journal of Language and Education 2024 Vol. 10 No. 4 P. 71–84
Introduction: Numerous algorithms have been proposed for the task of automatic morpheme segmentation of Russian words. Due to the differences in task formulation and datasets utilized, comparing the quality of these algorithms is challenging. It is unclear whether the errors in the models are due to the ineffectiveness of algorithms themselves or to errors and inconsistencies ...
Added: January 7, 2025
Derkacheva A., Frost G., Ermokhina K. et al., , in: 2023 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS).: IEEE, 2023. P. 1–4.
Many studies using convolutional neural networks, including in the field of satellite images, are aimed at recognizing clearly defined objects, such as cars or individual trees. Here we present the first results on mapping the growth stage of tundra shrubs, which is a ‘‘fuzzy’’ target for a network: there are no obvious geometric boundaries of ...
Added: March 22, 2023
Savchenko A., , in: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).: IEEE, 2022. P. 2358–2365.
In this paper, we consider the problem of real-time video-based facial emotion analytics, namely, facial expression recognition, prediction of valence and arousal and detection of action unit points. We propose the novel frame-level emotion recognition algorithm by extracting facial features with the single EfficientNet model pre-trained on Affect-Net. The predictions for sequential frames are smoothed ...
Added: August 29, 2022
Makarov I., Bakhanova M., Nikolenko S. et al., PeerJ Computer Science 2022 Vol. 8 Article e865
Depth estimation has been an essential task for many computer vision applications, especially in autonomous driving, where safety is paramount. Depth can be estimated not only with traditional supervised learning but also via a self-supervised approach that relies on camera motion and does not require ground truth depth maps. Recently, major improvements have been introduced ...
Added: February 1, 2022
Krinitskiy M., Alexandrova M., Verezemskaya P. et al., Remote Sensing 2021 Vol. 13 No. 2 Article 326
Total Cloud Cover (TCC) retrieval from ground-based optical imagery is a problem that has been tackled by several generations of researchers. The number of human-designed algorithms for the estimation of TCC grows every year. However, there has been no considerable progress in terms of quality, mostly due to the lack of systematic approach to the ...
Added: September 24, 2021
Dmitrii Maslov, Makarov I., , in: Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I* 1. Vol. 12861.: Springer, 2021. Ch. 38 P. 456–467.
In this paper, we study depth reconstruction via RGB-based, Sparse-Depth, and RGBd approaches. We showed that combination of RGB and Sparse Depth approach in RGBd scenario provides the best results. We also proved that the models performance can be further tuned via proper selection of architecture blocks and number of depth points guiding RGB-to-depth reconstruction. ...
Added: September 1, 2021
Kudriavtseva P., Kashkinov M., Kertész-Farkas A., Journal of Proteome Research 2021 Vol. 20 No. 10 P. 4708–4717
Spectrum annotation is a challenging task due to the presence of unexpected peptide fragmentation ions as well as the inaccuracy of the detectors of the spectrometers. We present a deep convolutional neural network, called Slider, which learns an optimal feature extraction in its kernels for scoring mass spectrometry (MS)/MS spectra to increase the number of ...
Added: August 30, 2021
Savchenko A., Demochkin K., Grechikhin I., Pattern Recognition 2022 Vol. 121 Article 108248
In this paper, a user modeling task is examined by processing mobile device gallery of photos and videos. We propose a novel engine for preferences prediction based on scene recognition, object detection and facial analysis. At first, all faces in a gallery are clustered, and all private photos and videos with faces from large clusters ...
Added: August 19, 2021
Makarov I., Nikolay Veldyaykin, Maxim Chertkov et al., , in: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '19).: NY: ACM, 2019. P. 204–210.
Sign languages are the main way for people from deaf community to communicate with other people. In this paper, we have compared several real-time sign language dactyl recognition systems using deep convolutional neural networks. Our system is able to recognize words from natural language gestured using signs for each letter. We evaluate our approach on ...
Added: July 10, 2021
Kharchevnikova A., Savchenko A., PeerJ Computer Science 2021 Vol. 7:e391 P. 1–18
The article is considering the problem of increasing the performance and accuracy of video face identification. We examine the selection of the several best video frames using various techniques for assessing the quality of images. In contrast to traditional methods with estimation of image brightness/contrast, we propose to utilize the deep learning techniques that estimate ...
Added: February 25, 2021
Savchenko A., Information Sciences 2021 Vol. 560 P. 370–385
A novel image recognition algorithm based on sequential three-way decisions is introduced to speed up the inference in a convolutional neural network. In contrast to the majority of existing studies, our approach does not require a special procedure to train a neural network, and thus it can be used with arbitrary architectures including pre-trained convolutional ...
Added: February 25, 2021