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http://dx.doi.org/10.9708/jksci.2022.27.10.011

A Study on AR Algorithm Modeling for Indoor Furniture Interior Arrangement Using CNN  

Ko, Jeong-Beom (Dept. of Computer Engineering, Kongju National University)
Kim, Joon-Yong (Dept. of IT Convergence Software, Seoul Theological University)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.10, 2022 , pp. 11-17 More about this Journal
Abstract
In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.
Keywords
3D Scanning; AR Labeling; Interior; Furniture; CNN;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Ko, Y. J., Lee, S. Y., Lee, J. O., 2016, Development of 3D Scanner Based on Laser Structured-light Image, Journal of Institute of Control, Robotics and Systems, 22:3 186-191, https://doi.org/10.5302/J.ICROS.2016.15.0204.   DOI
2 M. Jang, "Design of 3D Printer Based on SLA Using LSU and Test of Scanning Mechanism," Journal of the Korea Institute of Information and Communication Engineering, vol. 21, no.6, pp. 1225-1230, Jun. 2017.   DOI
3 S. Bernhardt, S. A. Nicolau, L. Soler and C. Doignon, "The status of augmented reality in laparoscopic surgery as of 2016," Med Image Anal, vol. 37, pp. 66-90, 2017.   DOI
4 Kow, Pu-Yun, et al. "Seamless integration of convolutional and back-propagation neural networks for regional multi-step-ahead PM2. 5 forecasting." Journal of Cleaner Production 261 (2020):121285.
5 Duarte, Amaro, and Esmitt Ramirez. "Interpreted Programming Language Extension for 3D Render on the Web." arXiv preprint arXiv:2004.01683 (2020).
6 M. WonJun, S. Youngho, and K. Dongwook, "Parameter Analysis for Time Reduction in Extracting SIFT Keypoints in the Aspect of Image Stitching," Journal of Broadcast Engineering, Vol.23, No.4, pp.559-573, July 2018.   DOI
7 Rashid, Muhammad, et al. "Object detection and classification: a joint selection and fusion strategy of deep convolutional neural network and SIFT point features." Multimedia Tools and Applications 78.12 (2019): 15751-15777.   DOI
8 Kim, Jae-Hyeong, and Seung-Ho Lee. "Measurement Technique of Indoor location Based on Markerless applicable to AR." Journal of IKEEE 25.2 (2021): 243-251.   DOI
9 Aboma, W. G. and Hirpa G, L., "Influence of 3D Printing FDM Process Parameters on Tensile Property of ULTEM 9085", Procedia Manufacturing, Vol. 30, pp. 331-338, 2019.   DOI
10 Kattenborn, Teja, et al. "Review on Convolutional Neural Networks (CNN) in vegetation remote sensing." ISPRS Journal of Photogrammetry and Remote Sensing 173 (2021): 24-49.   DOI
11 Rashevska, N. V. "Augmented reality and the prospects for applying its in the training of future engineers." October 2018.
12 Zhong, Bing, and Yubai Li. "Image feature point matching based on improved SIFT algorithm." 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC). IEEE, 2019.
13 Oh, Am-Suk. "Design and Implementation of Smart Home Remote Control Based on Internet of Things Service Platform." Journal of the Korea Institute of Information and Communication Engineering 22.12 (2018): 1563-1570.   DOI
14 J. Lee, Marker Evaluation Method Based on SIFT Descriptor for Effective Augmented Reality System Implementation, Master's thesis, Sunchon National University, Suncheon, Korea, pp.20-28, 2019.
15 Feng, M. Fukuda, Y. Feng, D. and Mizuta, M. (2015). "Nontarget Vision Sensor for RemoteMeasurement of Bridge Dynamic Response."Journal of Bridge Engineering, Vol. 20, (12).
16 Koo, Da Som, and Jeong Ran Lee. "The development of a wrist brace using 3D scanner and 3D printer." Fashion & Textile Research Journal 19.3 (2017): 312-319.   DOI