Dataset Open Access
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
Name | Size | |
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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 |
All versions | This version | |
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Views | 724 | 724 |
Downloads | 317 | 317 |
Data volume | 2.2 TB | 2.2 TB |
Unique views | 624 | 624 |
Unique downloads | 174 | 174 |