Sign Language Recognition Using Leap Motion

dc.creatorQuesada Quirós, Luis
dc.creatorLópez Herrera, Gustavo
dc.creatorGuerrero Blanco, Luis Alberto
dc.date.accessioned2018-04-16T21:48:09Z
dc.date.accessioned2019-04-25T15:04:02Z
dc.date.available2018-04-16T21:48:09Z
dc.date.available2019-04-25T15:04:02Z
dc.date.created2018-04-16T21:48:09Z
dc.date.issued2015-12-01
dc.identifierhttps://link.springer.com/chapter/10.1007/978-3-319-26401-1_26
dc.identifier978-3-319-26401-1
dc.identifier978-3-319-26400-4
dc.identifierhttp://hdl.handle.net/10669/74490
dc.identifier10.1007/978-3-319-26401-1_26
dc.identifier320-B5-291
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/2378448
dc.description.abstractSeveral million people around the world use signs as their main mean of communication. The advances in technologies to recognize such signs will make possible the computer supported interpretation of sign languages. There are more than 137 different sign language around the world; therefore, a system that interprets those languages could be beneficial to all, including the Deaf Community. This paper presents a system based on a hand tracking device called Leap Motion, used for signs recognition. The system uses a Support Vector Machine for sign classification. We performed three different evaluations of our system with over 24 people.
dc.languageen_US
dc.sourceQuesada L., López G., Guerrero L.A. (2015) Sign Language Recognition Using Leap Motion. In: García-Chamizo J., Fortino G., Ochoa S. (eds) Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information. Lecture Notes in Computer Science, vol 9454. Springer, Cham
dc.subjectAmerican sign language
dc.subjectLeap motion
dc.subjectSupport vector machine
dc.subjectAutomatic sign language recognition
dc.titleSign Language Recognition Using Leap Motion
dc.typeActas de congresos
dc.typeObjeto de conferencia


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