Abstract
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.
This work has been supported by the EU FP7 RUBICON project (contract no. 269914).
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Amato, G. et al. (2016). A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living. In: Lindgren, H., et al. Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). ISAmI 2016. Advances in Intelligent Systems and Computing, vol 476. Springer, Cham. https://doi.org/10.1007/978-3-319-40114-0_1
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DOI: https://doi.org/10.1007/978-3-319-40114-0_1
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