Sign language recognition model combining non-manual markers and handshapes
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| Autores: | , , |
|---|---|
| Formato: | contribución de congreso |
| Fecha de Publicación: | 2016 |
| Descripción: | People with disabilities have fewer opportunities. Technological developments should be used to help these people to have more opportunities. In this paper we present partial results of a research project which aims to help people with disabilities, specifically deaf and hard of hearing. We present a sign language recognition model. The model takes advantage of the natural user interfaces (NUI) and a classification algorithm (support vector machines). Moreover, we combine handshapes (signs) and non-manual markers (associated to emotions and face gestures) in the recognition process to enhance the sign language expressivity recognition. Additionally, non-manual markers representation is proposed. A model evaluation is also reported. |
| País: | Kérwá |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Kérwá |
| OAI Identifier: | oai:kerwa.ucr.ac.cr:10669/74426 |
| Acceso en línea: | https://link.springer.com/chapter/10.1007/978-3-319-48746-5_41 https://hdl.handle.net/10669/74426 |
| Palabra clave: | Sign language recognition Handshapes recognition Non-manual markers recognition Intel RealSense |