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Authors: Timothée Fréville ; Charles Hamesse ; Bênoit Pairet and Rob Haelterman

Affiliation: Royal Military Academy, Rue Hobbema 8, Brussels, Belgium

Keyword(s): Image Recognition, Floor Plans, Neural Networks, Synthetic Data.

Abstract: The development of visually compelling Virtual Reality (VR) environments for serious games is a complex task. Most environments are designed using game engines such as Unity or Unreal Engine and require hours if not days of work. However, most important information of indoor environments can be represented by floor plans. Those have been used in architecture for centuries as a fast and reliable way of depicting building configurations. Therefore, the idea of easing the creation of VR ready environments using floor plans is of great interest. In this paper we propose an automated framework to detect and classify objects in floor plans using a neural network trained with a custom floor plan dataset generator. We evaluate our system on three floor plans datasets: ROBIN (labelled), PFG (our own Procedural Floor plan Generation method) and 100 labelled samples from the CubiCasa Dataset

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Paper citation in several formats:
Fréville, T.; Hamesse, C.; Pairet, B. and Haelterman, R. (2023). Object Detection in Floor Plans for Automated VR Environment Generation. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 480-486. DOI: 10.5220/0011629300003417

@conference{visapp23,
author={Timothée Fréville. and Charles Hamesse. and Bênoit Pairet. and Rob Haelterman.},
title={Object Detection in Floor Plans for Automated VR Environment Generation},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP},
year={2023},
pages={480-486},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011629300003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP
TI - Object Detection in Floor Plans for Automated VR Environment Generation
SN - 978-989-758-634-7
IS - 2184-4321
AU - Fréville, T.
AU - Hamesse, C.
AU - Pairet, B.
AU - Haelterman, R.
PY - 2023
SP - 480
EP - 486
DO - 10.5220/0011629300003417
PB - SciTePress

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