| id |
caadria2018_044 |
| authors |
Inoue, Kazuya, Fukuda, Tomohiro, Cao, Rui and Yabuki, Nobuyoshi |
| year |
2018 |
| title |
Tracking Robustness and Green View Index Estimation of Augmented and Diminished Reality for Environmental Design - PhotoAR+DR2017 project |
| source |
T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 339-348 |
| doi |
https://doi.org/10.52842/conf.caadria.2018.1.339
|
| summary |
To assess an environmental design, augmented and diminished reality (AR/DR) have a potential to build a consensus more smoothly through the landscape simulation of new design visualization of the items to be assessed, such as the green view index. However, the current system is still considered to be impractical because it does not provide complete user experience. Thus, we aim to improve the robustness of the AR/DR system and to integrate the estimation of the green view index into the AR/DR system on a game engine. Further, we achieve an improved stable tracking by eliminating the outliers of the tracking reference points using the random sample consensus (RANSAC) method and by defining the tracking reference points over an extensive area of the AR/DR display. Additionally, two modules were implemented, among which one module is used to solve the occlusion problem while the other is used to estimate the green view index. The novel integrated AR/DR system with all modules was developed on the game engine. A mock design project was developed in an outdoor environment for simulation purposes, thereby verifying the applicability of the developed system. |
| keywords |
Environmental Design; Augmented Reality (AR); Diminished Reality (DR); Green View Index; Segmentation |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,939,774 bytes) |
| references |
Content-type: text/plain
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Badrinarayanan, V, Kendall, A and Cipolla, R (2017)
 SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
, IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), p. 2481-2495
|
|
|
|
|
Ding, Y, Fukuda, T, Yabuki, N and Motamedi, A (2016)
Automatic Measurement System of Visible Greenery Ratio Using Augmented Reality
, Proceedings of the 21st International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2016), p. 703-712
|
|
|
|
|
Fraundorfer, F and Scaramuzza, D (2012)
Visual Odometry : Part II: Matching, Robustness, Optimization, and Applications
, IEEE Robotics & Automation Magazine, 19, p. 79-90
|
|
|
|
|
Fukuda, T, Inoue, K and Yabuki, N (2017)
PhotoAR+DR2016 - Integrating Automatic Estimation of Green View Index and Augmented and Diminished Reality for Architectural Design Simulation
, Proceedings of eCAADe 2017, apienza University of Rome, Rome, Italy, p. 495-502
|
|
|
|
|
Klinker, G, Stricker, D and Reiners, D (2001)
Augmented Reality for Exterior Construction Applications
, Barfield, W and Caudell, T (eds), Augmented Reality and Wearable Computers, Lawrence Erlbaum Press, New Jersey, p. 397-427
|
|
|
|
|
Long, J, Shelhamer, E and Darrell, T (2015)
Fully Convolutional Networks for Semantic Segmentation
, the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), p. 3431-3440
|
|
|
|
|
Mori, S, Ikeda, S and Saito, H (2017)
A survey of diminished reality: Techniques for visually concealing, eliminating, and seeing through real objects
, IPSJ Transactions on Computer Vision and Applications, 9, p. 1-17
|
|
|
|
|
Portalés, C, Lerma, J.L. and Navarro, S (2010)
Augmented reality and photogrammetry: A synergy to visualize physical and virtual city environments
, ISPRS Journal of Photogrammetry and Remote Sensing, 65, p. 134-142
|
|
|
|
|
Ronneberger, O, Fischer, P and Brox, T (2015)
U-Net: Convolutional Networks for Biomedical Image Segmentation
, Medical Image Computing and Computer Assisted Intervention, 9351, p. 234-241
|
|
|
|
|
Tomasi, C and Kanade, T (1992)
Shape and motion from image streams under orthography: a factorization method
, International Journal of Computer Vision, 9, p. 137-154
|
|
|
|
|
Yang, J, Zhao, L, Mcbride, J and Gong, P (2009)
Can you see green? Assessing the visibility of urban forests in cities
, Landscape and Urban Planning, 91, p. 97-104
|
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|
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| last changed |
2022/06/07 07:50 |
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