基于Kinect2的传统舞蹈脚本实时三维运动手势识别

A. Emanuel, Andreas Widjaja
{"title":"基于Kinect2的传统舞蹈脚本实时三维运动手势识别","authors":"A. Emanuel, Andreas Widjaja","doi":"10.1109/ICACSIS.2018.8618251","DOIUrl":null,"url":null,"abstract":"This preliminary study presents a system capable of recognizing human gesture in real-time. The gesture is acquired from a Kinect2 sensor which provides skeleton joints represented by three-dimensional coordinate points. The model set consists of eight motion gestures is provided for basis of gesture recognition using Dynamic Time Warping (DTW) algorithm. DTW algorithm is utilized to identify in real time manner by measuring the shortest combined distances in x, y, and z coordinates in order to determined the matched gesture. It can be shown that the system is able to recognize these 8 motions in real time with some limitations. The findings of the this study will provide solid foundation of further research in which the ultimate goal of the research is to create system to automatically recognize sequence of motions in Indonesian traditional dances and convert them into standardized Resource Description Framework (RDF) scripts for the purpose of preserving these dances.","PeriodicalId":207227,"journal":{"name":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-Time 3-D Motion Gesture Recognition using Kinect2 as Basis for Traditional Dance Scripting\",\"authors\":\"A. Emanuel, Andreas Widjaja\",\"doi\":\"10.1109/ICACSIS.2018.8618251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This preliminary study presents a system capable of recognizing human gesture in real-time. The gesture is acquired from a Kinect2 sensor which provides skeleton joints represented by three-dimensional coordinate points. The model set consists of eight motion gestures is provided for basis of gesture recognition using Dynamic Time Warping (DTW) algorithm. DTW algorithm is utilized to identify in real time manner by measuring the shortest combined distances in x, y, and z coordinates in order to determined the matched gesture. It can be shown that the system is able to recognize these 8 motions in real time with some limitations. The findings of the this study will provide solid foundation of further research in which the ultimate goal of the research is to create system to automatically recognize sequence of motions in Indonesian traditional dances and convert them into standardized Resource Description Framework (RDF) scripts for the purpose of preserving these dances.\",\"PeriodicalId\":207227,\"journal\":{\"name\":\"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACSIS.2018.8618251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACSIS.2018.8618251","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

本初步研究提出了一个能够实时识别人类手势的系统。该手势由Kinect2传感器获取,该传感器提供由三维坐标点表示的骨骼关节。该模型集由8种运动手势组成,为动态时间扭曲(DTW)算法的手势识别提供了基础。DTW算法通过测量x、y、z坐标的最短组合距离来实时识别,从而确定匹配的手势。结果表明,该系统能够实时识别这8种运动,但存在一定的局限性。本研究的结果将为进一步的研究提供坚实的基础,研究的最终目标是创建一个系统,自动识别印度尼西亚传统舞蹈中的动作序列,并将其转换为标准化的资源描述框架(RDF)脚本,以保存这些舞蹈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time 3-D Motion Gesture Recognition using Kinect2 as Basis for Traditional Dance Scripting
This preliminary study presents a system capable of recognizing human gesture in real-time. The gesture is acquired from a Kinect2 sensor which provides skeleton joints represented by three-dimensional coordinate points. The model set consists of eight motion gestures is provided for basis of gesture recognition using Dynamic Time Warping (DTW) algorithm. DTW algorithm is utilized to identify in real time manner by measuring the shortest combined distances in x, y, and z coordinates in order to determined the matched gesture. It can be shown that the system is able to recognize these 8 motions in real time with some limitations. The findings of the this study will provide solid foundation of further research in which the ultimate goal of the research is to create system to automatically recognize sequence of motions in Indonesian traditional dances and convert them into standardized Resource Description Framework (RDF) scripts for the purpose of preserving these dances.
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