A Semantic Labeling of the Environment Based on What People Do
AbstractIn 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
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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.
Crespo J, Gómez C, Hernández A, Barber R. A Semantic Labeling of the Environment Based on What People Do. Sensors. 2017; 17(2):260.Chicago/Turabian Style
Crespo, Jonathan; Gómez, Clara; Hernández, Alejandra; Barber, Ramón. 2017. "A Semantic Labeling of the Environment Based on What People Do." Sensors 17, no. 2: 260.
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