基于MEMS加速度的步态识别

First International Conference on Availability, Reliability and Security (ARES'06) Pub Date : 2006-04-20 DOI:10.1109/ARES.2006.68

D. Gafurov, Kirsi Helkala, Torkjel Søndrol

{"title":"基于MEMS加速度的步态识别","authors":"D. Gafurov, Kirsi Helkala, Torkjel Søndrol","doi":"10.1109/ARES.2006.68","DOIUrl":null,"url":null,"abstract":"This paper presents an approach on recognising individuals based on 3D acceleration data from walking, which are collected using MEMS. Unlike most other gait recognition methods, which are based on video source, our approach uses walking acceleration in three directions: vertical, backward-forward and sideways. Using gait samples from 21 individuals and applying two methods, histogram similarity and cycle length, the equal error rates of 5% and 9% are achieved, respectively.","PeriodicalId":106780,"journal":{"name":"First International Conference on Availability, Reliability and Security (ARES'06)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"83","resultStr":"{\"title\":\"Gait recognition using acceleration from MEMS\",\"authors\":\"D. Gafurov, Kirsi Helkala, Torkjel Søndrol\",\"doi\":\"10.1109/ARES.2006.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an approach on recognising individuals based on 3D acceleration data from walking, which are collected using MEMS. Unlike most other gait recognition methods, which are based on video source, our approach uses walking acceleration in three directions: vertical, backward-forward and sideways. Using gait samples from 21 individuals and applying two methods, histogram similarity and cycle length, the equal error rates of 5% and 9% are achieved, respectively.\",\"PeriodicalId\":106780,\"journal\":{\"name\":\"First International Conference on Availability, Reliability and Security (ARES'06)\",\"volume\":\"97 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"83\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"First International Conference on Availability, Reliability and Security (ARES'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ARES.2006.68\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"First International Conference on Availability, Reliability and Security (ARES'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARES.2006.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 83

摘要

本文提出了一种基于微机电系统采集的三维行走加速度数据的个体识别方法。与大多数其他基于视频源的步态识别方法不同，我们的方法在三个方向上使用行走加速度:垂直、前后和侧向。利用21个个体的步态样本，采用直方图相似度和周期长度两种方法，错误率分别为5%和9%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Gait recognition using acceleration from MEMS

This paper presents an approach on recognising individuals based on 3D acceleration data from walking, which are collected using MEMS. Unlike most other gait recognition methods, which are based on video source, our approach uses walking acceleration in three directions: vertical, backward-forward and sideways. Using gait samples from 21 individuals and applying two methods, histogram similarity and cycle length, the equal error rates of 5% and 9% are achieved, respectively.

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

First International Conference on Availability, Reliability and Security (ARES'06)

自引率

0.00%

发文量