{"title":"使用多个kinect进行实时性能捕获","authors":"Seongmin Baek, Myunggyu Kim","doi":"10.1109/ICTC.2014.6983241","DOIUrl":null,"url":null,"abstract":"There have been many cases applying recognized user movements in games as low-cost sensor such as Microsoft Kinect and Asus Xtion have appeared, but there is limitation in capturing user movements with one sensor. This paper uses multiple kinect sensors to propose a method to capture user performance. By solving calibration and synchronization problems between sensors and appropriately combining input data, stable performance capture is possible even in occlusion of body parts.","PeriodicalId":299228,"journal":{"name":"2014 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"210 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Real-time performance capture using multiple Kinects\",\"authors\":\"Seongmin Baek, Myunggyu Kim\",\"doi\":\"10.1109/ICTC.2014.6983241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There have been many cases applying recognized user movements in games as low-cost sensor such as Microsoft Kinect and Asus Xtion have appeared, but there is limitation in capturing user movements with one sensor. This paper uses multiple kinect sensors to propose a method to capture user performance. By solving calibration and synchronization problems between sensors and appropriately combining input data, stable performance capture is possible even in occlusion of body parts.\",\"PeriodicalId\":299228,\"journal\":{\"name\":\"2014 International Conference on Information and Communication Technology Convergence (ICTC)\",\"volume\":\"210 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Information and Communication Technology Convergence (ICTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTC.2014.6983241\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Information and Communication Technology Convergence (ICTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTC.2014.6983241","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time performance capture using multiple Kinects
There have been many cases applying recognized user movements in games as low-cost sensor such as Microsoft Kinect and Asus Xtion have appeared, but there is limitation in capturing user movements with one sensor. This paper uses multiple kinect sensors to propose a method to capture user performance. By solving calibration and synchronization problems between sensors and appropriately combining input data, stable performance capture is possible even in occlusion of body parts.