{"title":"罗伯特导航的快速手势识别","authors":"Xiaoping Sun, Zhijie Wang","doi":"10.1109/BMEI.2013.6747018","DOIUrl":null,"url":null,"abstract":"We propose a fast algorithm for automatically recognizing several common hand gestures and its application background is navigation of robot. The rapidity of this system reflects in four aspects: definition of gesture control signals, selection of gesture model, segmentation of hand gesture area, and features extraction. The experimental results show that the system can respond to gesture commands quickly and have good performance in real-time and accuracy.","PeriodicalId":163211,"journal":{"name":"2013 6th International Conference on Biomedical Engineering and Informatics","volume":"134 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Rapid gesture recognition for robert navigation\",\"authors\":\"Xiaoping Sun, Zhijie Wang\",\"doi\":\"10.1109/BMEI.2013.6747018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a fast algorithm for automatically recognizing several common hand gestures and its application background is navigation of robot. The rapidity of this system reflects in four aspects: definition of gesture control signals, selection of gesture model, segmentation of hand gesture area, and features extraction. The experimental results show that the system can respond to gesture commands quickly and have good performance in real-time and accuracy.\",\"PeriodicalId\":163211,\"journal\":{\"name\":\"2013 6th International Conference on Biomedical Engineering and Informatics\",\"volume\":\"134 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 6th International Conference on Biomedical Engineering and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BMEI.2013.6747018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 6th International Conference on Biomedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2013.6747018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We propose a fast algorithm for automatically recognizing several common hand gestures and its application background is navigation of robot. The rapidity of this system reflects in four aspects: definition of gesture control signals, selection of gesture model, segmentation of hand gesture area, and features extraction. The experimental results show that the system can respond to gesture commands quickly and have good performance in real-time and accuracy.
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