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ORCID: https://orcid.org/0000-0001-9873-8502 and García Santos, Narciso
ORCID: https://orcid.org/0000-0002-0397-894X
(2015).
Unsupervised high-quality soccer field segmentation.
En: "International Symposium on Consumer Electronics (ISCE 2015)", 24/06/2015 - 26/06/2015, Madrid, Spain. pp. 1-2.
https://doi.org/10.1109/ISCE.2015.7177808.
| Título: | Unsupervised high-quality soccer field segmentation |
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| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | International Symposium on Consumer Electronics (ISCE 2015) |
| Fechas del Evento: | 24/06/2015 - 26/06/2015 |
| Lugar del Evento: | Madrid, Spain |
| Título del Libro: | International Symposium on Consumer Electronics (ISCE 2015) |
| Fecha: | 2015 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Soccer; segmentation; chromaticity; automatic; unsupervised; field |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Señales, Sistemas y Radiocomunicaciones |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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Field segmentation is a fundamental step in many soccer applications. However, despite its importance, the existing segmentation algorithms are not able to provide successful results in complex scenarios. Moreover, they require the manual selection of several parameters, hindering their usability. Here, an unsupervised field segmentation strategy based on the estimation of the probability density function of the green chromacity of the image is proposed. Results show its ability to provide high-quality results in a wide variety of scenarios.
| ID de Registro: | 42770 |
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| Identificador DC: | https://oa.upm.es/42770/ |
| Identificador OAI: | oai:oa.upm.es:42770 |
| Identificador DOI: | 10.1109/ISCE.2015.7177808 |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 17 Jul 2016 07:46 |
| Ultima Modificación: | 17 Jul 2016 07:46 |
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