Objectives We introduce a RGB+S dataset named “Industrial Human Action Recognition Dataset” (InHARD) from a real-world setting for industrial human action recognition with over 2 million frames, collected from 16 distinct subjects. This dataset contains 13 different industrial action classes and over 4800 action samples. The introduction of this dataset should allow us the study and development of various learning techniques for the task of human actions analysis inside industrial environments involving human robot collaborations. Read 00-README.txt for detailed download instructions. More details on the dataset at https://github.com/vhavard/InHARD This work has been performed at the CESI LINEACT : https://recherche.cesi.fr/inhard-industrial-human-action-recognition-dataset/ ; Parts of this work has been performed within the AGIRH project and has been funded in the framework of the Normandy Regional Council
InHARD - Industrial Human Action Recognition Dataset in the Context of Industrial Collaborative Robotics
2020-09-07
Forschungsdaten
Elektronische Ressource
Englisch
Human Action Recognition , HAR , Deep Learning , Human-Robot Collaboration , HRC , Industry 4.0 , RGB , Skeleton , LSTM , RNN
DDC: | 629 |
BASE | 2023
|Springer Verlag | 2020
|Industrial Robotics : New Paradigms
GWLB - Gottfried Wilhelm Leibniz Bibliothek | 2020
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