{"title":"基于Kinect传感器的印度古典舞腿部姿势识别研究","authors":"S. Saha, Shreya Ghosh, A. Konar, R. Janarthanan","doi":"10.1109/ICHCI-IEEE.2013.6887795","DOIUrl":null,"url":null,"abstract":"This paper proposes a simple yet a novel technique to recognize leg postures in Indian classical dance by making use of a Kinect sensor. The sensor device has the ability to track the skeleton of the subject with the help of a visible camera and an IR camera coupled to an IR laser and diffraction grating. Twenty five leg postures from `Odissi', an Indian Classical dance have been used for the evaluation our proposed algorithm. This methodology extracts eight features, which in turn can be categorized under three levels of symmetry viz. the vertical symmetry, the horizontal symmetry and the angular symmetry. Finally a similarity function is devised which is the basis of the leg posture recognition technique. This method provides better human computer interaction and also aims at spreading the dance form for e-learning purpose. The proposed algorithm can be applied for any dance form for leg posture recognition purposes. It gives 86.75% accuracy with five subjects.","PeriodicalId":419263,"journal":{"name":"2013 International Conference on Human Computer Interactions (ICHCI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A study on leg posture recognition from Indian classical dance using Kinect sensor\",\"authors\":\"S. Saha, Shreya Ghosh, A. Konar, R. Janarthanan\",\"doi\":\"10.1109/ICHCI-IEEE.2013.6887795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a simple yet a novel technique to recognize leg postures in Indian classical dance by making use of a Kinect sensor. The sensor device has the ability to track the skeleton of the subject with the help of a visible camera and an IR camera coupled to an IR laser and diffraction grating. Twenty five leg postures from `Odissi', an Indian Classical dance have been used for the evaluation our proposed algorithm. This methodology extracts eight features, which in turn can be categorized under three levels of symmetry viz. the vertical symmetry, the horizontal symmetry and the angular symmetry. Finally a similarity function is devised which is the basis of the leg posture recognition technique. This method provides better human computer interaction and also aims at spreading the dance form for e-learning purpose. The proposed algorithm can be applied for any dance form for leg posture recognition purposes. It gives 86.75% accuracy with five subjects.\",\"PeriodicalId\":419263,\"journal\":{\"name\":\"2013 International Conference on Human Computer Interactions (ICHCI)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Human Computer Interactions (ICHCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICHCI-IEEE.2013.6887795\",\"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 International Conference on Human Computer Interactions (ICHCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICHCI-IEEE.2013.6887795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A study on leg posture recognition from Indian classical dance using Kinect sensor
This paper proposes a simple yet a novel technique to recognize leg postures in Indian classical dance by making use of a Kinect sensor. The sensor device has the ability to track the skeleton of the subject with the help of a visible camera and an IR camera coupled to an IR laser and diffraction grating. Twenty five leg postures from `Odissi', an Indian Classical dance have been used for the evaluation our proposed algorithm. This methodology extracts eight features, which in turn can be categorized under three levels of symmetry viz. the vertical symmetry, the horizontal symmetry and the angular symmetry. Finally a similarity function is devised which is the basis of the leg posture recognition technique. This method provides better human computer interaction and also aims at spreading the dance form for e-learning purpose. The proposed algorithm can be applied for any dance form for leg posture recognition purposes. It gives 86.75% accuracy with five subjects.