A Semantic Labeling of the Environment Based on What People Do

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dc.contributor.author Crespo Herrero, Jonathan
dc.contributor.author Gómez Blázquez, Clara
dc.contributor.author Hernández Silva, Alejandra Carolina
dc.contributor.author Barber Castaño, Ramón Ignacio
dc.date.accessioned 2019-01-14T10:06:35Z
dc.date.available 2019-01-14T10:06:35Z
dc.date.issued 2017-01-29
dc.identifier.bibliographicCitation Crespo,J., Gómez,C., Hernández,A., Barber,R. (2017). A Semantic Labeling of the Environment Based on What People Do. Sensors, 17 (2), 260.
dc.identifier.issn 1424-8220
dc.identifier.uri http://hdl.handle.net/10016/27880
dc.description.abstract In this work, a system is developed for semantic labeling of locations based on what people do. This system is useful for semantic navigation of mobile robots. The system differentiates environments according to what people do in them. Background sound, number of people in a room and amount of movement of those people are items to be considered when trying to tell if people are doing different actions. These data are sampled, and it is assumed that people behave differently and perform different actions. A support vector machine is trained with the obtained samples, and therefore, it allows one to identify the room. Finally, the results are discussed and support the hypothesis that the proposed system can help to semantically label a room.
dc.description.abstract The research leading to these results has received funding from the RoboCity2030-III-CMproject (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+Den la Comunidad de Madrid and cofunded by Structural Funds of the EU and NAVEGASEAUTOCOGNAVproject (DPI2014-53525-C3-3-R), funded by Ministerio de Economía y Competitividad of Spain.
dc.description.sponsorship The research leading to these results has received funding from the RoboCity2030-III-CMproject (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+Den la Comunidad de Madrid and cofunded by Structural Funds of the EU and NAVEGASEAUTOCOGNAVproject (DPI2014-53525-C3-3-R), funded by Ministerio de Economía y Competitividad of Spain.
dc.format.extent 21
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher MDPI
dc.rights © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Semantic labeling
dc.subject.other Semantic navigation
dc.subject.other Mobile robotics
dc.subject.other Detecting people
dc.subject.other Environment classification
dc.subject.other range data
dc.subject.other Robot
dc.subject.other Classification
dc.subject.other Recognition
dc.subject.other Places
dc.title A Semantic Labeling of the Environment Based on What People Do
dc.type article
dc.subject.eciencia Robótica e Informática Industrial
dc.identifier.doi https://doi.org/10.3390/s17020260
dc.rights.accessRights openAccess
dc.relation.projectID Comunidad de Madrid. S2013/MIT-2748/RoboCity2030-III-CMproject
dc.relation.projectID Gobierno de España. DPI2014-53525-C3-3-R
dc.type.version publishedVersion
dc.identifier.publicationissue 2
dc.identifier.publicationtitle Sensors
dc.identifier.publicationvolume 17
dc.identifier.uxxi AR/0000019674
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