A Deep Hybrid Architecture for Human Activity Recognition
Sofia Stylianou-Nikolaidou, Ioannis Vernikos, Eirini Mathe, Evaggelos Spyrou · 2021
In this paper we present early results of a novel approach for human activity recognition, focusing on activities of daily living. Our approach is multimodal, i.e., it combines RGB, depth and skeletal data measurements. Moreover, it is based on a novel hybrid deep neural network architecture that combines a convolutional neural network, a long short term memory network and it is evaluated using a publicly available dataset.