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Published August 25, 2024 | Version v1
Dataset Open

CarDA - Car door Assembly Activities Dataset

  • 1. FORTH Institute of Computer Science
  • 2. ROR icon National Technical University of Athens
  • 3. ROR icon Institute of Communication and Computer Systems
  • 1. ROR icon National Technical University of Athens

Description

The proposed multi-modal dataset for car door assembly activities, noted as CarDA [1], comprises a set of time-synchronized multi-camera RGB-D videos and
motion capture data acquired during car door assembly activities performed by real-line workers in a real manufacturing environment.

[1] Konstantinos Papoutsakis, Nikolaos Bakalos, Konstantinos Fragkoulis, Athena Zacharia, Georgia Kapetadimitri, and Maria Pateraki. A vision-based framework for human behavior understanding in industrial assembly lines. In Proceedings of the European Conference on Computer Vision (ECCV) Workshops - T-CAP 2024 Towards a Complete Analysis of People: Fine-grained Understanding for Real-World Applications, 2024.

CarDA subset Α

It contains visual data in the form of .svo (RGB-D acquired using StereoLabs ZED 2 sensors), mp4 videos, .bvh files for 3D human pose data (ground truth), and annotation data (to be added in v2 of the dataset).

 

CarDA subset B

Contains visual data in the form of .svo (RGB-D acquired using StereoLabs ZED 2 sensors), mp4 videos, and annotation data.  

  • ws10 - svo - mp4

Three pairs of RGB-D videos (.svo) acquired by two StereoLabs ZED 2 different stereo cameras placed in the real workplace are provided.

Each pair of RGB-D videos demonstrates a complete car door task cycle for workstation WS10 of the assembly line.

MP4 videos are also available. Extracted using the left camera of the stereo pair of each camera.

Annotation data for the task cycles are provided in the xls file related to the temporal segmentation and semantics of the assembly activities performed and the duration any of the supported EAWS-based postures occurred during an assembly activity. 

  • ws20 - svo - mp4

Six pairs of RGB-D videos (svo) acquired by two StereoLabs ZED 2 different stereo cameras placed in the real workplace are provided.

MP4 videos are also available. Extracted using the left camera of the stereo pair of each camera.

Each pair of RGB-D videos demonstrates a complete car door task cycle for workstation WS20 of the assembly line.

Annotation data for the task cycles are provided in the xls file related to the temporal segmentation and semantics of the assembly activities performed and the duration any of the supported EAWS-based postures occurred during an assembly activity. 

  • ws30 - svo - mp4

Three pairs of RGB-D videos (svo) acquired by two StereoLabs ZED 2 different stereo cameras placed in the real workplace are provided.

Each pair of RGB-D videos demonstrates a complete car door task cycle for workstation WS30 of the assembly line.

MP4 videos are also available. Extracted using the left camera of the stereo pair of each camera.

Annotation data for the task cycles are provided in the xls file related to the temporal segmentation and semantics of the assembly activities performed and the duration any of the supported EAWS-based postures occurred during an assembly activity. 

 

Files

car_door_coordinate_system.jpg

Files (14.5 GB)

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Additional details

Funding

European Commission
FELICE – FlExible assembLy manufacturIng with human-robot Collaboration and digital twin modEls 101017151
European Commission
SOPRANO – Socially-Acceptable and Trustworthy Human-Robot Teaming for Agile Industries 101120990

Software

Programming language
Python, C++

References

  • Konstantinos Papoutsakis, Nikolaos Bakalos, Konstantinos Fragkoulis, Athena Zacharia, Georgia Kapetadimitri, and Maria Pateraki. A vision-based framework for human behavior understanding in industrial assembly lines. In Proceedings of the European Conference on Computer Vision (ECCV) Workshops - T-CAP 2024 Towards a Complete Analysis of People: Fine-grained Understanding for Real-World Applications, 2024.