| id |
ijac202119205 |
| authors |
Fukuda, Tomohiro; Marcos Novak, Hiroyuki Fujii, Yoann Pencreach |
| year |
2021 |
| title |
Virtual reality rendering methods for training deep learning, analysing landscapes, and preventing virtual reality sickness |
| source |
International Journal of Architectural Computing 2021, Vol. 19 - no. 2, 190207 |
| summary |
Virtual reality (VR) has been proposed for various purposes such as design studies, presentation, simulation and communication in the field of computer-aided architectural design. This paper explores new roles for VR; in particular, we propose rendering methods that consist of post-processing rendering, segmentation rendering and shadow-casting rendering for more-versatile approaches in the use of data. We focus on the creation of a dataset of annotated images, composed of paired foreground-background and semantic-relevant images, in addition to traditional immersive rendering for training deep learning neural networks and analysing landscapes. We also develop a camera velocity rendering method using a customised segmentation rendering technique that calculates the linear and angular velocities of the virtual camera within the VR space at each frame and overlays a colour on the screen according to the velocity value. Using this velocity information, developers of VR applications can improve the animation path within the VR space and prevent VR sickness. We successfully applied the developed methods to urban design and a design project for a building complex. In conclusion, the proposed method was evaluated to be both feasible and effective. |
| keywords |
Virtual reality, rendering, shader, deep learning, landscape analytics, virtual reality sickness, Fourth Industrial Revolution, computer-aided architectural design |
| series |
journal |
| email |
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| references |
Content-type: text/plain
|
Abdelhameed WA. (2012)
 Micro-Simulation function to display textual data in virtual reality
, Int J Archit Comput; 10(2): 205218.
|
|
|
|
|
As I, Siddharth P and Prithwish B. (2018)
Artificial intelligence in architecture: generating conceptual design via deep learning
, Int J Archit Comp; 16(4): 306327.
|
|
|
|
|
Barrι-Brisebois C, Halen H, Wihlidal G, et al. (2019)
Hybrid rendering for real-time ray tracing
, Haines E and Akenine-Mφller T (eds) Rayt gems. Berkeley, CA: Apress.
|
|
|
|
|
Bryson S. (1996)
Virtual reality in scientific visualization
, Commun ACM; 39(5): 6271.
|
|
|
|
|
Cao R, Fukuda T and Yabuki N. (2019)
Quantifying visual environment by semantic segmentation using deep learning
, Proceedings of CAADRIA; 2: 7180.
|
|
|
|
|
Cevette MJ, Stepanek J, Cocco D, et al. (2012)
Oculo-vestibular recoupling using galvanic vestibular stimulation to mitigate simulator sickness
, Aviat Space Environ Med; 83(6): 549555(7).
|
|
|
|
|
Dai J, He K and Sun J. (2016)
Instance-aware semantic segmentation via multi-task network cascades
, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV: IEEE.
|
|
|
|
|
Dichgans J and Brandt T. (1978)
Visual-vestibular interaction: effects on self-motion perception and postural control
, Held R, Leibowitz HW and Teubner HL (eds) Perception (Handbook of sensory psychology). Vol. 8. New York: Springer, pp. 756795.
|
|
|
|
|
Dorta T and LaLande P. (1998)
The impact of virtual reality on the design process, digital design studios: do computers make a difference?
, Proceedings of the 18th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) Quιbec City, Canada, pp. 138163.
|
|
|
|
|
Dorta T, Kinayoglu G and Hoffmann M. (2016)
Hyve3D and the 3D Cursor: architectural co-design with freedom in virtual reality
, Int J Archit Comput; 14(2): 87102.
|
|
|
|
|
Eloy S, Ourique L, Woessner U, et al. (2018)
How present am I three virtual reality facilities testing the fear of falling
, Proceedings of eCAADe Volume 2, pp. 717726.
|
|
|
|
|
Forte M and Pietroni E. (2009)
3D Collaborative environments in archaeology: experiencing the reconstruction of the past
, Int J Archit Comput; 7(1): 5776.
|
|
|
|
|
Fukuda T, Kaga A, Izumi H, et al. (2009)
Citizen participatory design method using VR and A Blog as a media in the process
, Int J Archit Comput; 7(2): 217233.
|
|
|
|
|
Fukuda T, Nada H, Adachi H, et al. (2017)
Integration of a structure from motion into virtual and augmented reality for architectural and urban simulation: demonstrated in real architectural and urban projects
, Commun Comput Inform Sci; 724: 6077.
|
|
|
|
|
Groen EL and Bos JE. (2008)
Simulator sickness depends on frequency of the simulator motion mismatch: an observation
, Presence Virtual Augmented Reality; 17(6): 584593.
|
|
|
|
|
Hernandez LA, Taibo J, Blanco D, et al. (2007)
Physically walking in digital spaces a virtual reality installation for exploration of historical heritage
, Inter J Archit Comput; 5(3): 487509.
|
|
|
|
|
Higuchi T. (1988)
Visual and spatial structure of landscapes
, Cambridge, MA: MIT Press.
|
|
|
|
|
Hosokawa M, Fukuda T, Yabuki N, et al. (2016)
Integrating CFD and VR for indoor thermal environment design feedback
, Proceedings of the 21st International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2016), pp. 663672.
|
|
|
|
|
Ikeno K, Fukuda T and Yabuki N. (2020)
Automatic generation of horizontal building mask images by using a 3d model with aerial photographs for deep learning
, Proceedings of eCAADe; 2: 271278.
|
|
|
|
|
Kennedy RS, Lane NE and Berbaum KS. (1993)
Simulator sickness questionnaire (SSQ): a new method for quantifying simulator sickness
, Int J Aviation Psychol; 3(3): 203220.
|
|
|
|
| last changed |
2024/04/17 14:29 |
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