Shih-Yao Lin, Chuen-Kai Shie, Chu-Song Chen, Y. Hung
{"title":"Freehand Push-Gesture Recognition via 3D Palm Trajectory Modeling","authors":"Shih-Yao Lin, Chuen-Kai Shie, Chu-Song Chen, Y. Hung","doi":"10.1145/2739999.2740005","DOIUrl":null,"url":null,"abstract":"This paper aims at improving the recognition of 3D push-hand gesture, which can trigger a target selection command with our hands in the air. Although general 3D push-gesture recognizers have been developed and widely used for this purpose, a severe weakness of the current push-recognizers is that they are instable to askew-pushing problems that happen frequently in practice. It is because that the push trajectory of our hand is not always a straightforward movement due to the anatomy of human, but would vary depending on the location of the target relative to the users. We explore the 3D palm trajectories of push-gestures in different locations around the user, and propose a 3D push-gesture modeling approach by learning 3D palm trajectories to solve the askew-click problem. We evaluate the proposed recognizers on a click-gesture dataset, and compare it with the prior arts of forward-push recognizers. Experimental results demonstrate that our approach achieves higher recognition accuracies than existing approaches.","PeriodicalId":115346,"journal":{"name":"Proceedings of the Third International Symposium of Chinese CHI","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Third International Symposium of Chinese CHI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2739999.2740005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper aims at improving the recognition of 3D push-hand gesture, which can trigger a target selection command with our hands in the air. Although general 3D push-gesture recognizers have been developed and widely used for this purpose, a severe weakness of the current push-recognizers is that they are instable to askew-pushing problems that happen frequently in practice. It is because that the push trajectory of our hand is not always a straightforward movement due to the anatomy of human, but would vary depending on the location of the target relative to the users. We explore the 3D palm trajectories of push-gestures in different locations around the user, and propose a 3D push-gesture modeling approach by learning 3D palm trajectories to solve the askew-click problem. We evaluate the proposed recognizers on a click-gesture dataset, and compare it with the prior arts of forward-push recognizers. Experimental results demonstrate that our approach achieves higher recognition accuracies than existing approaches.