Data for: Interior construction state recognition with 4D BIM registered image sequences

Published: 9 Nov 2017 | Version 1 | DOI: 10.17632/rskgn5f8y8.1
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Description of this data

For the evaluation of the "Interior construction state recognition with 4D BIM registered image sequences" framework, three exemplary videos were selected that document the radiator and drywall activity states. All the videos were recorded at the renovation of the IC building on the campus of the Ruhr-Universität Bochum, Germany, with the monocular rear camera of a tablet PC. The first video part shows the non-present radiator and installed drywall panels, the second video part shows the non-installed radiator and the plastered drywall state, and the third video part contains the appearance of the radiator and the painted drywall state. The goal of this experiment was to test the ability of the final statement about the activity state under the influence of all previous steps starting from the initial registration, over fine and rough pose estimation towards the activity state recognition.

Experiment data files

peer reviewed

This data is associated with the following peer reviewed publication:

Interior construction state recognition with 4D BIM registered image sequences

Published in: Automation in Construction

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  • Version 1

    2017-11-09

    Published: 2017-11-09

    DOI: 10.17632/rskgn5f8y8.1

    Cite this dataset

    Koch, Christian; König, Markus; Kropp, Christopher (2017), “Data for: Interior construction state recognition with 4D BIM registered image sequences”, Mendeley Data, v1 http://dx.doi.org/10.17632/rskgn5f8y8.1

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Categories

Engineering, Computer Vision, Civil Engineering, Informatics, Image Registration

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CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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