Human Activity Recognition for Packing Processes using CNN-biLSTM
Alberto Angulo, Jessica Beltrán, Luis Adrián Castro · 2023
Human activity recognition has several applications in healthcare, sports, and industrial settings. In the latter, it can monitor industry workers and evaluate if the required activities are appropriately performed. In this paper, we employ state-of-the-art Deep Learning techniques to recognize ten distinct packing activities performed by sixteen participants from the Openpack dataset. Our proposed architecture combines data from various sensors and leverages Convolutional Neural Networks and Long Short-Term Memory networks to process spatial and temporal data. Additionally, we incorporate Transformers into our network, resulting in an improved F1-Score performance of 98.21.