Dataset Open Access

Logistic Activity Recognition Challenge (LARa) – A Motion Capture and Inertial Measurement Dataset

Niemann, Friedrich; Reining, Christopher; Moya Rueda, Fernando; Altermann, Erik; Nair, Nilah Ravi; Steffens, Janine Anika; Fink, Gernot A.; ten Hompel, Michael

LARa is the first freely accessible logistics-dataset for human activity recognition. In the ’Innovationlab Hybrid Services in Logistics’ at TU Dortmund University, two picking and one packing scenarios with 14 subjects were recorded using OMoCap, IMUs, and an RGB camera. 758 minutes of recordings were labeled by 12 annotators in 474 person-hours. The subsequent revision was carried out by 4 revisers in 143 person-hours. All the given data have been labeled and categorized into 8 activity classes and 19 binary coarse-semantic descriptions, also called attributes.

 

If you use this dataset for research, please cite the following paper: “LARa: Creating a Dataset for Human Activity Recognition in Logistics Using Semantic Attributes”, Sensors 2020, DOI: 10.3390/s20154083

Acknowledgement: The work on this publication was supported by Deutsche Forschungsgemeinschaft (DFG) in the context of the project Fi799/10-2, HO2403/14-2 "Transfer Learning for Human Activity Recognition in Logistics".
Files (31.0 GB)
Name Size
annotation and revision tool.zip
md5:6fcf6c993cf0039778d84c833787d64a
2.8 GB Download
attrib_network.zip
md5:aff95bd9b1b950bcad01640108d3ee08
1.4 GB Download
class_network.zip
md5:5848f5e6c2ac264088d04e8f7fc4773b
1.4 GB Download
IMU data.zip
md5:c83d54b8b48e6abaee464f683bdddc66
613.6 MB Download
OMoCap data.zip
md5:9055d879ec6c0e63a8e3190276f06a66
5.9 GB Download
recording protocol.pdf
md5:47ca225166a709d91a26a70e49ac3835
2.7 MB Download
RGB videos.zip
md5:d4dc90d9605a72ae1c649281485f4a39
18.8 GB Download
555
253
views
downloads
All versions This version
Views 555555
Downloads 253253
Data volume 1.7 TB1.7 TB
Unique views 477477
Unique downloads 138138

Share

Cite as