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GAIT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORKS
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Соколова А. И., Konushin A.
In press
In this work we investigate the problem of people recognition by their gait. For this task, we implement deep learning approach using the optical flow as the main source of motion information and combine neural feature extraction with the additional embedding of descriptors for representation improvement. In order to find the best heuristics, we compare several deep neural network architectures, learning and classification strategies. The experiments were made on two popular datasets for gait recognition, so we investigate their advantages and disadvantages and the transferability of considered methods.
In book
Vol. XLII-2/W4. , [б.и.], 2017
Makarov I., Vladimir Aliev, Gerasimova Olga et al., , in : Adjunct Proceedings of 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct). : NY : IEEE, 2017. P. 93-94.
In this paper, we discuss a semi-dense depth map interpolation method based on convolutional neural network. We propose a compact neural network architecture with loss function defined as Euclidean distance in the feature space of VGG-16 neural network used for deep visual recognition. The suggested solution shows state-of-art performance on synthetic and real datasets. Together ...
Added: August 5, 2017
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
Kharchevnikova A., Savchenko A., В кн. : Материалы XXIII международной научно-технической конференции «Информационные системы и технологии-2017». : [б.и.], 2017. С. 864-869.
Рассматривается задача построения интеллектуальных систем контекстной рекламы с автоматической настройкой на потенциальные предпочтения пользователя. Выполнен аналитический обзор современных публикаций, посвященных распознаванию пола и возраста по видеоизображению лица, в том числе на основе глубоких сверточных нейронных сетей. Проведен сравнительный анализ способов агрегации решений, полученных при распознавании каждого видеокадра. Приведены результаты экспериментального исследования их точности и быстродействия. ...
Added: October 24, 2017
Savchenko A., , in : Proceedings of International Joint Conference on Neural Networks 2020 (IJCNN 2020). : Piscataway : IEEE, 2020. P. 1-8.
In this paper the problem of high computational complexity of deep convolutional nets in image recognition is considered. An existing framework of adaptive neural networks is extended by appending the separate classifier to intermediate layers. The hierarchical representations of the input image are sequentially analyzed. If the first classifier returns rather high confidence score, the ...
Added: October 15, 2020
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
Соколова А. Д., Savchenko A., В кн. : Материалы XXIII международной научно-технической конференции «Информационные системы и технологии-2017». : [б.и.], 2017. С. 870-875.
Рассматривается задача структурирования информации в программных системах видеонаблюдения с помощью группирования видеоданных, в которых присутствуют идентичные лица. Сделан акцент на эффективную кластеризацию видеопоследовательностей с использованием сверточных нейронных сетей для извлечения характерных признаков. Разработан новый алгоритм кластеризации фрагментов видео на основе технологий глубокого обучения и статистического подхода. Приведены предварительные результаты экспериментального исследования точности и быстродействия предложенного ...
Added: October 24, 2017
Соколова А. И., Konushin A., Programming and Computer Software 2019 Vol. 45 No. 4 P. 213-220
Human gait is an important biometric index that allows to identify a person at a great distance without direct contact. Due to these qualities, which other popular identifiers such as fingerprints or iris do not have, the recognition of a person by the manner of walking has become very common in various areas where video ...
Added: October 31, 2019
Кривогин М. С., Право. Журнал Высшей школы экономики 2017 № 2 С. 80-89
В статье анализируется соотношение правового регулирования специальной и биометрической категорий персональных данных. Выявляется ряд отличительных критериев, на основе которых строится разграничение между названными категориями. Рассматривается проблема осуществления обработки биометрических персональных данных, сделанных общедоступными субъектом персональных данных. Проведено исследование российской и зарубежной доктрины, нормативноправовых актов, отечественной судебной практики в области правового регулирования различных категорий персональных данных. ...
Added: October 29, 2018
Alisa Korinevskaya, Makarov I., , in : Proceedings of IEEE International Symposium on Mixed and Augmented Reality (ISMAR'18). : NY : IEEE, 2019. P. 117-122.
Depth map super-resolution is a challenging computer vision problem. In this paper, we present two deep convolutional neural networks solving the problem of single depth map super-resolution. Both networks learn residual decomposition and trained with specific perceptual loss improving sharpness and perceptive quality of the upsampled depth map. Several experiments on various depth super-resolution benchmark ...
Added: July 29, 2019
Savchenko A., , in : Proceedings of International Joint Conference on Neural Networks 2020 (IJCNN 2020). : Piscataway : IEEE, 2020. P. 1-8.
In this paper a new formulation of event recognition task is examined: it is required to predict event categories given a gallery of images, for which albums (groups of photos corresponding to a single event) are unknown. The novel two-stage approach is proposed. At first, features are extracted in each photo using the pre-trained convolutional ...
Added: October 15, 2020
Makarov I., 501502591, Maxim Chertkov et al., , in : 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). : NY : IEEE, 2019. P. 726-729.
In this paper, we compare several real-time sign language dactyl recognition systems and present a new model based on deep convolutional neural networks. These systems are able to recognize Russian alphabet letters presented as static signs in Russian Sign language used by people from deaf community. In such an approach, we recognize words from Russian ...
Added: July 29, 2019
Kharchevnikova A., Savchenko A., Компьютерная оптика 2020 Т. 44 № 4 С. 618-626
В работе рассматривается задача извлечения предпочтений пользователя по его фотоальбому. Предложен новый подход на основе автоматического порождения текстовых описаний фотографий и последующей классификации таких описаний. Проведен анализ известных методов создания аннотаций по изображению на основе свёрточных и рекуррентных (Long short-term memory) нейронных сетей. С использованием набора данных Google’s Conceptual Captions обучены новые модели, в которых ...
Added: September 16, 2020
Sokolova A., Konushin A., IET Biometrics 2019 Vol. 8 No. 2 P. 134-143
Human gait or walking manner is a biometric feature that allows identification of a person when other biometric features such as the face or iris are not visible. In this study, the authors present a new pose-based convolutional neural network model for gait recognition. Unlike many methods that consider the full-height silhouette of a moving ...
Added: October 31, 2019
Petrov I., Shakhuro V., Konushin A., IET Computer Vision 2018 Vol. 12 No. 5 P. 578-585
The authors consider the problem of human pose estimation using probabilistic convolutional neural networks. They explore ways to improve human pose estimation accuracy on standard pose estimation benchmarks MPII human pose and Leeds Sports Pose (LSP) datasets using frameworks for probabilistic deep learning. Such frameworks transform deterministic neural network into a probabilistic one and allow ...
Added: March 14, 2018
Demochkin K., Savchenko A., , in : Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers. Vol. 11832.: Cham : Springer, 2019. Ch. 26. P. 291-297.
In this paper we focus on the problem of multi-label image recognition for visually-aware recommender systems. We propose a two stage approach in which a deep convolutional neural network is firstly fine-tuned on a part of the training set. Secondly, an attention-based aggregation network is trained to compute the weighted average of visual features in ...
Added: December 22, 2019
Savchenko A., Miasnikov E., , in : Advances in Intelligent Data Analysis XVIII (IDA 2020). Vol. 12080.: Cham : Springer, 2020. Ch. 33. P. 418-430.
In this paper, we consider the problem of event recognition on single images. In contrast to conventional fine-tuning of convolutional neural networks (CNN), we proposed to use image captioning, i.e., a generative model that converts images to textual descriptions. The motivation here is the possibility to combine conventional CNNs with a completely different approach in ...
Added: May 17, 2020
Miasnikov E., Savchenko A., , in : Proceedings of International Conference on Image Analysis and Recognition (ICIAR 2020). Vol. 12131.: Cham : Springer, 2020. Ch. 9. P. 83-94.
Food analysis is one of the most important parts of user preference prediction engines for recommendation systems in the travel domain. In this paper, we describe and study the neural network method that allows you to recognize food in a gallery of photos taken with mobile devices. The described method consists of three main stages, ...
Added: October 1, 2020
Arseev S., Konushin A., Lutov V., Programming and Computer Software 2018 Vol. 44 No. 4 P. 258-265
This work is focused on person identification task in video sequences. For this task we propose two complementing solutions, which can be applied in different cases: gait and visual recognition. For gait recognition three kinds of features are used: anthropometric features, based on the length of the skeleton segments; relative distance features, based on relative ...
Added: October 31, 2019
Cham : Springer, 2023
Added: November 29, 2023
Anastasiia D. Sokolova, Angelina S. Kharchevnikova, Savchenko A., , in : Analysis of Images, Social Networks and Texts. 6th International Conference, 2017, Revised Selected Papers. Vol. 10716.: Cham : Springer, 2018. P. 223-230.
In this paper we propose the two-stage approach of organizing information in video surveillance systems. At first, the faces are detected in each frame and a video stream is split into sequences of frames with face region of one person. Secondly, these sequences (tracks) that contain identical faces are grouped using face verification algorithms and ...
Added: May 2, 2018
Cham : Springer, 2020
This book focuses on the core areas of computing and their applications in the real world. Presenting papers from the Computing Conference 2020 covers a diverse range of research areas, describing various detailed techniques that have been developed and implemented.
The Computing Conference 2020, which provided a venue for academic and industry practitioners to share new ...
Added: July 7, 2020
Cham : Springer, 2018
The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018. The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; ...
Added: October 31, 2018
Sokolova Anastasiia, Kharchevnikova Angelina, Savchenko A., Lecture Notes in Computer Science 2018 Vol. 10716 P. 223-230
In this paper we propose the two-stage approach of organizing information in video surveillance systems. At first, the faces are detected in each frame and a video stream is split into sequences of frames with face region of one person. Secondly, these sequences (tracks) that contain identical faces are grouped using face verification algorithms and ...
Added: October 24, 2017
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