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InHARD - Industrial Human Action Recognition Dataset in the Context of Industrial Collaborative Robotics

Mejdi Dallel, Vincent Havard, David Baudry, Xavier Savatier

Year
2020
Citations
2

Abstract

<strong>Objectives</strong> 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.<br> Read <strong>00-README.txt</strong> 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/

Keywords

Artificial intelligenceRoboticsContext (archaeology)Action recognitionAction (physics)Computer scienceRobotBiology

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