PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Amato G., Bacciu D., Chessa S., Dragone M., Gallicchio C., Gennaro C., Lozano H., Micheli A., O'Hare G. M., Renteria A., Vairo C. A benchmark dataset for human activity recognition and ambient assisted living. In: ISAmI 2016 - Ambient Intelligence- Software and Applications. 7th International Symposium on Ambient Intelligence (Sevilla, Spain, 1-3 June 2016). Proceedings, pp. 1 - 9. Helena Lindgren, Juan F. De Paz, Paulo Novais, Antonio Fernández-Caballero, Hyun Yoe, Andres Jiménez Ramírez, Gabriel Villarrubia (eds.). (Advances in Intelligent Systems and Computing). Springer, 2016.
 
 
Abstract
(English)
We present a data benchmark for the assessment of human activity recognition solutions, collected as part of the EU FP7 RUBICON project, and available to the scientific community. The dataset provides fully annotated data pertaining to numerous user activities and comprises synchronized data streams collected from a highly sensor-rich home environment. A baseline activity recognition performance obtained through an Echo State Network approach is provided along with the dataset.
URL: http://link.springer.com/chapter/10.1007/978-3-319-40114-0_1
DOI: 10.1007/978-3-319-40114-0_1
Subject Ambient assisted living
Human Activity Recognition
Datasets
C.2 COMPUTER-COMMUNICATION NETWORKS. Wireless communication
I.2.9 ARTIFICIAL INTELLIGENCE. Robotics


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