{"title":"基于kinect传感器的吉他技能学习性能检测方法研究","authors":"Yoshitaka Kashiwagi, Youji Ochi, Yasuo Miyoshi, Yuichiro Mori, Ryo Okamoto","doi":"10.1109/GCCE.2015.7398550","DOIUrl":null,"url":null,"abstract":"Recent years, in many research fields, the approach of utilizing motion sensors have attracted attention. In educational technology researches, it appears to be common in supporting physical skill learning. We have developed a system to detect the guitar performance using Microsoft Kinect Sensor (hereinafter, Kinect). In this paper, we describe about the detection of the guitar area and the performance motion.","PeriodicalId":363743,"journal":{"name":"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A study of performance detection method for a guitar skill learning using kinect sensor\",\"authors\":\"Yoshitaka Kashiwagi, Youji Ochi, Yasuo Miyoshi, Yuichiro Mori, Ryo Okamoto\",\"doi\":\"10.1109/GCCE.2015.7398550\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent years, in many research fields, the approach of utilizing motion sensors have attracted attention. In educational technology researches, it appears to be common in supporting physical skill learning. We have developed a system to detect the guitar performance using Microsoft Kinect Sensor (hereinafter, Kinect). In this paper, we describe about the detection of the guitar area and the performance motion.\",\"PeriodicalId\":363743,\"journal\":{\"name\":\"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GCCE.2015.7398550\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 4th Global Conference on Consumer Electronics (GCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2015.7398550","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A study of performance detection method for a guitar skill learning using kinect sensor
Recent years, in many research fields, the approach of utilizing motion sensors have attracted attention. In educational technology researches, it appears to be common in supporting physical skill learning. We have developed a system to detect the guitar performance using Microsoft Kinect Sensor (hereinafter, Kinect). In this paper, we describe about the detection of the guitar area and the performance motion.