{"title":"用于便携式手势界面的框架","authors":"Sébastien Wagner, B. Alefs, C. Picus","doi":"10.1109/FGR.2006.54","DOIUrl":null,"url":null,"abstract":"Gesture recognition is a valuable extension for interaction with portable devices. This paper presents a framework for interaction by hand gestures using a head mounted camera system. The framework includes automatic activation using AdaBoost hand detection, tracking of chromatic and luminance color modes based on adaptive mean shift and pose recognition using template matching of the polar histogram. The system achieves 95% detection rate and 96% classification accuracy at real time processing, for a non-static camera setup and cluttered background","PeriodicalId":109260,"journal":{"name":"7th International Conference on Automatic Face and Gesture Recognition (FGR06)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Framework for a portable gesture interface\",\"authors\":\"Sébastien Wagner, B. Alefs, C. Picus\",\"doi\":\"10.1109/FGR.2006.54\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Gesture recognition is a valuable extension for interaction with portable devices. This paper presents a framework for interaction by hand gestures using a head mounted camera system. The framework includes automatic activation using AdaBoost hand detection, tracking of chromatic and luminance color modes based on adaptive mean shift and pose recognition using template matching of the polar histogram. The system achieves 95% detection rate and 96% classification accuracy at real time processing, for a non-static camera setup and cluttered background\",\"PeriodicalId\":109260,\"journal\":{\"name\":\"7th International Conference on Automatic Face and Gesture Recognition (FGR06)\",\"volume\":\"143 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"7th International Conference on Automatic Face and Gesture Recognition (FGR06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FGR.2006.54\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Conference on Automatic Face and Gesture Recognition (FGR06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FGR.2006.54","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gesture recognition is a valuable extension for interaction with portable devices. This paper presents a framework for interaction by hand gestures using a head mounted camera system. The framework includes automatic activation using AdaBoost hand detection, tracking of chromatic and luminance color modes based on adaptive mean shift and pose recognition using template matching of the polar histogram. The system achieves 95% detection rate and 96% classification accuracy at real time processing, for a non-static camera setup and cluttered background
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