步态识别方法在生物特征任务中的人体识别

Sergiy V. Purish, Mykhaylo V. Lobachev
{"title":"步态识别方法在生物特征任务中的人体识别","authors":"Sergiy V. Purish, Mykhaylo V. Lobachev","doi":"10.15276/hait.06.2023.1","DOIUrl":null,"url":null,"abstract":"This article focuses on defining the problem of solving the problem of human identification by means of gait recognition in biometric identification systems. In order to determine the prospects of using gait recognition methods for human identification, a generalized model of a biometric identification system was considered, the main modules of the system were identified and a brief description of each module was provided. Next, the basic requirements for human biometric features were identified, the main biometric features were considered, and the features of their use in biometric identification systems were determined. The issue of using gait as a biometric identifier was also considered. It has been determined that the use of human gait allows to get rid of two main obstacles in the construction of biometric identification systems: users are not required to provide personal biometric information in advance, and the system does not require specialized equipment. Also, the issue of multi-view gait recognition was considered. Multi-view gait recognition involves capturing gait data from different angles and using this data to improve recognition accuracy. This approach has shown great promise in challenging scenarios such as low lighting conditions. Next, we analyzed scientific works in the field of gait recognition. It was determined that gait recognition methods can be divided into template-based and non-template-based methods. Template-based methods are aimed at obtaining patterns of torso or leg movements, i.e. they usually focus on the dynamics of movement in space or on spatio-temporal methods. Non-template-based methods consider shape and its features as more relevant characteristics, i.e., human recognition are performed using measurements that reflect the shape of the person. Next, we consider the use of different datasets in the process of training and testing human gait recognition methods. The main datasets were identified and their characteristics and features were collected. We considered the presence of various characteristics in the datasets, as well as the means of representing information about human gait. The research has identified the main problems and challenges facing researchers in this area, as well as the main trends in the field of human gait recognition in biometric identification systems.","PeriodicalId":375628,"journal":{"name":"Herald of Advanced Information Technology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gait recognition methods in the task of biometric human identification\",\"authors\":\"Sergiy V. Purish, Mykhaylo V. Lobachev\",\"doi\":\"10.15276/hait.06.2023.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article focuses on defining the problem of solving the problem of human identification by means of gait recognition in biometric identification systems. In order to determine the prospects of using gait recognition methods for human identification, a generalized model of a biometric identification system was considered, the main modules of the system were identified and a brief description of each module was provided. Next, the basic requirements for human biometric features were identified, the main biometric features were considered, and the features of their use in biometric identification systems were determined. The issue of using gait as a biometric identifier was also considered. It has been determined that the use of human gait allows to get rid of two main obstacles in the construction of biometric identification systems: users are not required to provide personal biometric information in advance, and the system does not require specialized equipment. Also, the issue of multi-view gait recognition was considered. Multi-view gait recognition involves capturing gait data from different angles and using this data to improve recognition accuracy. This approach has shown great promise in challenging scenarios such as low lighting conditions. Next, we analyzed scientific works in the field of gait recognition. It was determined that gait recognition methods can be divided into template-based and non-template-based methods. Template-based methods are aimed at obtaining patterns of torso or leg movements, i.e. they usually focus on the dynamics of movement in space or on spatio-temporal methods. Non-template-based methods consider shape and its features as more relevant characteristics, i.e., human recognition are performed using measurements that reflect the shape of the person. Next, we consider the use of different datasets in the process of training and testing human gait recognition methods. The main datasets were identified and their characteristics and features were collected. We considered the presence of various characteristics in the datasets, as well as the means of representing information about human gait. The research has identified the main problems and challenges facing researchers in this area, as well as the main trends in the field of human gait recognition in biometric identification systems.\",\"PeriodicalId\":375628,\"journal\":{\"name\":\"Herald of Advanced Information Technology\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Herald of Advanced Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15276/hait.06.2023.1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Herald of Advanced Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15276/hait.06.2023.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文重点阐述了生物识别系统中利用步态识别解决人体识别问题的定义问题。为了确定步态识别方法在人体识别中的应用前景,考虑了生物特征识别系统的广义模型,对系统的主要模块进行了识别,并对各模块进行了简要描述。其次,确定了人体生物特征的基本要求,考虑了主要的生物特征,确定了它们在生物识别系统中的应用特征。研究了步态作为生物特征识别的问题。已经确定,使用人体步态可以消除构建生物特征识别系统的两个主要障碍:用户不需要事先提供个人生物特征信息,系统不需要专门的设备。同时,对多视角步态识别问题进行了研究。多视角步态识别涉及从不同角度捕获步态数据,并利用这些数据来提高识别精度。这种方法在低光照条件等具有挑战性的场景中显示出巨大的前景。其次,分析了步态识别领域的相关研究成果。确定了步态识别方法可分为基于模板的方法和非基于模板的方法。基于模板的方法旨在获得躯干或腿部运动的模式,即它们通常侧重于空间运动的动态或时空方法。非基于模板的方法将形状及其特征视为更相关的特征,即使用反映人的形状的测量来执行人类识别。接下来,我们考虑在训练和测试人类步态识别方法的过程中使用不同的数据集。识别主要数据集,收集其特征和特征。我们考虑了数据集中存在的各种特征,以及表示人类步态信息的方法。研究确定了该领域研究人员面临的主要问题和挑战,以及生物特征识别系统中人体步态识别领域的主要趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait recognition methods in the task of biometric human identification
This article focuses on defining the problem of solving the problem of human identification by means of gait recognition in biometric identification systems. In order to determine the prospects of using gait recognition methods for human identification, a generalized model of a biometric identification system was considered, the main modules of the system were identified and a brief description of each module was provided. Next, the basic requirements for human biometric features were identified, the main biometric features were considered, and the features of their use in biometric identification systems were determined. The issue of using gait as a biometric identifier was also considered. It has been determined that the use of human gait allows to get rid of two main obstacles in the construction of biometric identification systems: users are not required to provide personal biometric information in advance, and the system does not require specialized equipment. Also, the issue of multi-view gait recognition was considered. Multi-view gait recognition involves capturing gait data from different angles and using this data to improve recognition accuracy. This approach has shown great promise in challenging scenarios such as low lighting conditions. Next, we analyzed scientific works in the field of gait recognition. It was determined that gait recognition methods can be divided into template-based and non-template-based methods. Template-based methods are aimed at obtaining patterns of torso or leg movements, i.e. they usually focus on the dynamics of movement in space or on spatio-temporal methods. Non-template-based methods consider shape and its features as more relevant characteristics, i.e., human recognition are performed using measurements that reflect the shape of the person. Next, we consider the use of different datasets in the process of training and testing human gait recognition methods. The main datasets were identified and their characteristics and features were collected. We considered the presence of various characteristics in the datasets, as well as the means of representing information about human gait. The research has identified the main problems and challenges facing researchers in this area, as well as the main trends in the field of human gait recognition in biometric identification systems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信