Methods of gait recognition in video

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 var...

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Main Authors: Anna Ilyinichna Sokolova, Anton Sergeevitch Konushin
Format: Article
Language:English
Published: Ivannikov Institute for System Programming of the Russian Academy of Sciences 2019-04-01
Series:Труды Института системного программирования РАН
Subjects:
Online Access:https://ispranproceedings.elpub.ru/jour/article/view/1146
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author Anna Ilyinichna Sokolova
Anton Sergeevitch Konushin
author_facet Anna Ilyinichna Sokolova
Anton Sergeevitch Konushin
author_sort Anna Ilyinichna Sokolova
collection DOAJ
description 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 surveillance systems can be used. With the development of computer vision techniques, a variety of approaches for human identification by movements in a video appear. These approaches are based both on natural biometric characteristics (human skeleton, silhouette, and their change during walking) and abstract features trained automatically which do not have physical justification. Modern methods combine classical algorithms of video and image analysis and new approaches that show excellent results in related tasks of computer vision, such as human identification by face and appearance or action and gesture recognition. However, due to the large number of conditions that can affect the walking manner of a person itself and its representation in video, the problem of identifying a person by gait still does not have a sufficiently accurate solution. Many methods are overfitted by the conditions presented in the databases on which they are trained, which limits their applicability in real life. In this paper, we provide a survey of state-of-the-art methods of gait recognition, their analysis and comparison on several popular video collections and for different formulations of the problem of recognition. We additionally reveal the problems that prevent the final solution of gait identification challenge.
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spelling doaj.art-219ae238d3a44656a0a3bba08e3908742022-12-22T01:44:12ZengIvannikov Institute for System Programming of the Russian Academy of SciencesТруды Института системного программирования РАН2079-81562220-64262019-04-01311698210.15514/ISPRAS-2019-31(1)-51144Methods of gait recognition in videoAnna Ilyinichna Sokolova0Anton Sergeevitch Konushin1Национальный исследовательский университет Высшая школа экономикиМосковский государственный университет им. М.В. ЛомоносоваHuman 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 surveillance systems can be used. With the development of computer vision techniques, a variety of approaches for human identification by movements in a video appear. These approaches are based both on natural biometric characteristics (human skeleton, silhouette, and their change during walking) and abstract features trained automatically which do not have physical justification. Modern methods combine classical algorithms of video and image analysis and new approaches that show excellent results in related tasks of computer vision, such as human identification by face and appearance or action and gesture recognition. However, due to the large number of conditions that can affect the walking manner of a person itself and its representation in video, the problem of identifying a person by gait still does not have a sufficiently accurate solution. Many methods are overfitted by the conditions presented in the databases on which they are trained, which limits their applicability in real life. In this paper, we provide a survey of state-of-the-art methods of gait recognition, their analysis and comparison on several popular video collections and for different formulations of the problem of recognition. We additionally reveal the problems that prevent the final solution of gait identification challenge.https://ispranproceedings.elpub.ru/jour/article/view/1146походкабиометриясилуэтнейронные сетиидентификация
spellingShingle Anna Ilyinichna Sokolova
Anton Sergeevitch Konushin
Methods of gait recognition in video
Труды Института системного программирования РАН
походка
биометрия
силуэт
нейронные сети
идентификация
title Methods of gait recognition in video
title_full Methods of gait recognition in video
title_fullStr Methods of gait recognition in video
title_full_unstemmed Methods of gait recognition in video
title_short Methods of gait recognition in video
title_sort methods of gait recognition in video
topic походка
биометрия
силуэт
нейронные сети
идентификация
url https://ispranproceedings.elpub.ru/jour/article/view/1146
work_keys_str_mv AT annailyinichnasokolova methodsofgaitrecognitioninvideo
AT antonsergeevitchkonushin methodsofgaitrecognitioninvideo