MOPED25: A multimodal dataset of full-body pose and motion in occupational tasks
MOPED25: A multimodal dataset of full-body pose and motion in occupational tasks
About this item
Full title
Author / Creator
Li, Li , Xie, Ziyang and Xu, Xu
Publisher
United States: Elsevier Ltd
Journal title
Language
English
Formats
Publication information
Publisher
United States: Elsevier Ltd
Subjects
More information
Scope and Contents
Contents
In recent years, there has been a trend of using images and deep neural network-based computer vision algorithms to perform postural evaluation in workplace safety and ergonomics community. The performance of the computer vision algorithms, however, heavily relies on the generalizability of the posture dataset that was used for algorithm training....
Alternative Titles
Full title
MOPED25: A multimodal dataset of full-body pose and motion in occupational tasks
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_miscellaneous_2458724387
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2458724387
Other Identifiers
ISSN
0021-9290
E-ISSN
1873-2380
DOI
10.1016/j.jbiomech.2020.110086
