Dataset Open Access

Logistic Activity Recognition Challenge (LARa Version 02) – A Motion Capture and Inertial Measurement Dataset

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


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  <dc:creator>Niemann, Friedrich</dc:creator>
  <dc:creator>Reining, Christopher</dc:creator>
  <dc:creator>Moya Rueda, Fernando</dc:creator>
  <dc:creator>Bas, Hülya</dc:creator>
  <dc:creator>Altermann, Erik</dc:creator>
  <dc:creator>Nair, Nilah Ravi</dc:creator>
  <dc:creator>Steffens, Janine Anika</dc:creator>
  <dc:creator>Fink, Gernot A.</dc:creator>
  <dc:creator>ten Hompel, Michael</dc:creator>
  <dc:date>2022-02-16</dc:date>
  <dc:description>LARa Version 02 is a 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 16 subjects were recorded using an optical marker-based Motion Capturing system (OMoCap), Inertial Measurement Units (IMUs), and an RGB camera. Each subject was recorded for one hour (960 minutes in total). All the given data have been labeled and categorised into eight activity classes and 19 binary coarse-semantic descriptions, also called attributes. In total, the dataset contains 221 unique attribute representations.

You can find the latest version of the annotation tool here: https://github.com/wilfer9008/Annotation_Tool_LARa

Upgrade:


	Subject 15 and 16 added
	OMoCap raw data added (c3d, csv)
	Second IMU set added (MotionMiners Sensors)
	OMoCap data: file names from subject 01 to subject 06 corrected
	OMoCap data: additional annotated data added
	OMoCap and IMU data (Mbientlab and MotionMiners Sensors): Annotation errors corrected
	OMoCap Networks added (all for Window Size of 200 frames (1sec.)) 
	
		tCNN_classes
		tCNN-IMU_classes
		tCNN_attrib
		tCNN-IMU_attrib 
	
	
	Mbientlab Networks added (all for Window Size of 100 frames (1sec.))
	
		tCNN_classes
		tCNN-IMU_classes
		tCNN_attrib
		tCNN-IMU_attrib
	
	
	Protocol extended (now README file)
	List of unique attribute representations added (csv)


 

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.

If you use the Mbientlab Networks, please cite the following paper: “From Human Pose to On-Body Devices for Human-Activity Recognition”, 25th International Conference on Pattern Recognition (ICPR), 2021, DOI: 10.1109/ICPR48806.2021.9412283.

If you have any questions about the dataset, please contact friedrich.niemann@tu-dortmund.de.</dc:description>
  <dc:description>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".</dc:description>
  <dc:identifier>https://zenodo.org/record/5761276</dc:identifier>
  <dc:identifier>10.5281/zenodo.5761276</dc:identifier>
  <dc:identifier>oai:zenodo.org:5761276</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.3390/s20154083</dc:relation>
  <dc:relation>doi:10.3390/s20154083</dc:relation>
  <dc:relation>doi:10.3390/s20154083</dc:relation>
  <dc:relation>doi:10.5281/zenodo.5680951</dc:relation>
  <dc:relation>doi:10.1109/ICPR48806.2021.9412283</dc:relation>
  <dc:relation>doi:10.1109/PerComWorkshops48775.2020.9156170</dc:relation>
  <dc:relation>doi:10.1109/PerComWorkshops51409.2021.9431062</dc:relation>
  <dc:relation>arxiv:arXiv:2111.04564</dc:relation>
  <dc:relation>doi:10.5281/zenodo.5680951</dc:relation>
  <dc:relation>doi:10.5281/zenodo.3862781</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc/4.0/legalcode</dc:rights>
  <dc:subject>Human Activity Recognition</dc:subject>
  <dc:subject>Attribute-based Representation</dc:subject>
  <dc:subject>Dataset</dc:subject>
  <dc:subject>Motion Capturing</dc:subject>
  <dc:subject>Intertial Measurement Unit</dc:subject>
  <dc:subject>Accelerometer</dc:subject>
  <dc:subject>Annotation</dc:subject>
  <dc:subject>Warehousing</dc:subject>
  <dc:subject>Logistics</dc:subject>
  <dc:title>Logistic Activity Recognition Challenge (LARa Version 02) – A Motion Capture and Inertial Measurement Dataset</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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