The HA4M dataset: Multi-Modal Monitoring of an assembly task for Human Action recognition in Manufacturing.

Autor: Cicirelli G; Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council of Italy, Bari, Italy. grazia.cicirelli@stiima.cnr.it., Marani R; Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council of Italy, Bari, Italy., Romeo L; Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council of Italy, Bari, Italy., Domínguez MG; Department of Mathematics and Computer Science, Universidad de La Rioja, Logroño, Spain., Heras J; Department of Mathematics and Computer Science, Universidad de La Rioja, Logroño, Spain., Perri AG; Department of Electric and Information Engineering, Polytechnical University of Bari, Bari, Italy., D'Orazio T; Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council of Italy, Bari, Italy.
Jazyk: angličtina
Zdroj: Scientific data [Sci Data] 2022 Dec 02; Vol. 9 (1), pp. 745. Date of Electronic Publication: 2022 Dec 02.
DOI: 10.1038/s41597-022-01843-z
Abstrakt: This paper introduces the Human Action Multi-Modal Monitoring in Manufacturing (HA4M) dataset, a collection of multi-modal data relative to actions performed by different subjects building an Epicyclic Gear Train (EGT). In particular, 41 subjects executed several trials of the assembly task, which consists of 12 actions. Data were collected in a laboratory scenario using a Microsoft® Azure Kinect which integrates a depth camera, an RGB camera, and InfraRed (IR) emitters. To the best of authors' knowledge, the HA4M dataset is the first multi-modal dataset about an assembly task containing six types of data: RGB images, Depth maps, IR images, RGB-to-Depth-Aligned images, Point Clouds and Skeleton data. These data represent a good foundation to develop and test advanced action recognition systems in several fields, including Computer Vision and Machine Learning, and application domains such as smart manufacturing and human-robot collaboration.
(© 2022. The Author(s).)
Databáze: MEDLINE
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