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Sensors 2017, 17(2), 260; doi:10.3390/s17020260

A Semantic Labeling of the Environment Based on What People Do

Department of Systems Engineering and Automation, University Carlos III of Madrid, 28911, Spain
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Academic Editors: Stefan Bosse, Ansgar Trächtler, Klaus-Dieter Thoben, Berend Denkena and Dirk Lehmhus
Received: 27 October 2016 / Revised: 19 January 2017 / Accepted: 20 January 2017 / Published: 29 January 2017
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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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. View Full-Text
Keywords: semantic labeling; semantic navigation; mobile robotics; detecting people; environment classification semantic labeling; semantic navigation; mobile robotics; detecting people; environment classification
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Crespo, J.; Gómez, C.; Hernández, A.; Barber, R. A Semantic Labeling of the Environment Based on What People Do. Sensors 2017, 17, 260.

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