A VR-based indoor visualization system from floorplan images with deep learning

Hao Fu; Mitsunori Makino

doi:10.1117/12.2625978

30 April 2022 A VR-based indoor visualization system from floorplan images with deep learning

Hao Fu, Mitsunori Makino

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 121771G (2022) https://doi.org/10.1117/12.2625978
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

In this paper, we propose a system to represent a 3D virtual house based on the given floorplan images, through which a user can understand intuitively and efficiently interior furnishing condition. The proposed system adopts a learning-based approach in the use of a convolutional neural network with customized dataset, which allows us to acquire high-accuracy semantic information of diverse components of the house, e.g., walls, toilet and area of balcony, from input floorplan image. Then, constructing an interactive virtual environment with Head-Mounted-Display (HMD), the system enables the user to adjust arbitrarily the position of furniture with various sizes, and prompts whether the selected furniture can be placed in a specific position through an intuitive way of expression.

Citation Download Citation

Hao Fu and Mitsunori Makino "A VR-based indoor visualization system from floorplan images with deep learning", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 121771G (30 April 2022); https://doi.org/10.1117/12.2625978

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