A Deep Neural Architecture for Kitchen Activity Recognition. Granada, R., Monteiro, J., Barros, R. C., & Meneguzzi, F. In The Florida Artificial Intelligence Research Society Conference (FLAIRS), 2017.
A Deep Neural Architecture for Kitchen Activity Recognition [pdf]Paper  abstract   bibtex   
Computer-based human activity recognition of daily living has recently attracted much interest due to its applicability to ambient assisted living. Such applications require the automatic recognition of high-level activities composed of multiple actions performed by human beings in a given environment. We propose a deep neural architecture for kitchen activity recognition, which uses an ensemble of machine learning models and hand-crafted features to extract more information of the data. Experiments show that our approach achieves the state-of-the-art for identifying cooking actions in a wellknown kitchen dataset.

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