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Volume: 33 | Article ID: art00014
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Generating a Hand Pose Data Set for Vision Based Manual Assembly Assistance Systems
Christian Jauch
Julia Denecke
Marco Huber
  DOI :  10.2352/ISSN.2470-1173.2021.18.3DIA-119  Published Online :  January 2021
Abstract

Current assistance systems for manual assembly reduce the efficiency of the worker by being invasive in the workflow. To restore the efficiency and at the same time to maintain the benefits of assistance systems, real time hand pose estimation can be used. However, no suitable data set is available for training such application specific detectors. In the presented work, a data set is generated that allows the use of different work gloves and prepares the overlay of realistic hand textures. We use low cost data gloves for hand pose tracking and a RGBD camera to capture the data set with 30 data points per second. This low cost approach is presented in an application for the manual assembly scenario, although transfer of the method to other scenarios is possible.

Journal Title : Electronic Imaging
Publisher Name : Society for Imaging Science and Technology
Publisher Location : IS&T 7003 Kilworth Lane, Springfield, VA 22151 USA
Subject Areas :
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 DOI 10.2352/ISSN.2470-1173.2021.18.3DIA-119
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  Cite this article 

Christian Jauch, Julia Denecke, Marco Huber, "Generating a Hand Pose Data Set for Vision Based Manual Assembly Assistance Systems"  in Proc. IS&T Int’l. Symp. on Electronic Imaging: 3D Imaging and Applications,  2021,  pp 119-1 - 119-7,  https://doi.org/10.2352/ISSN.2470-1173.2021.18.3DIA-119

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Copyright © Society for Imaging Science and Technology 2021
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane, Springfield, VA 22151 USA
10.2352/ISSN.2470-1173.2021.18.3DIA-119
2470-1173(20210118)2021:18L.1191;1-
ei_24701173_v2021n18_input_r1/s11.xml
/ist/ei/2021/00002021/00000018/art00014
Articles
Generating a Hand Pose Data Set for Vision Based Manual Assembly Assistance Systems
JauchChristian
DeneckeJulia
HuberMarco
18012021
2021
18
119-1
119-7
2021
Current assistance systems for manual assembly reduce the efficiency of the worker by being invasive in the workflow. To restore the efficiency and at the same time to maintain the benefits of assistance systems, real time hand pose estimation can be used. However, no suitable data set is available for training such application specific detectors. In the presented work, a data set is generated that allows the use of different work gloves and prepares the overlay of realistic hand textures. We use low cost data gloves for hand pose tracking and a RGBD camera to capture the data set with 30 data points per second. This low cost approach is presented in an application for the manual assembly scenario, although transfer of the method to other scenarios is possible.
Manual assemblyHand pose estimationDataset generationAssistance systemsData GloveRGBD data