International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Precision comparison of 3D photogrammetry scans according to the number and resolution of images

  • Park, JaeWook (Department of Plasma Bio Display, Kwangwoon University) ;
  • Kim, YunJung (School of SW Advanced Convergence Technology, Inha University) ;
  • Kim, Lyoung Hui (Department of Visual Design, Seoul Institute of the Arts) ;
  • Kwon, SoonChul (Graduate School of Smart Convergence, Kwangwoon University) ;
  • Lee, SeungHyun (Ingenium College, Kwangwoon University)
  • Received : 2021.05.03
  • Accepted : 2021.05.10
  • Published : 2021.06.30
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Abstract

With the development of 3D graphics software and the speed of computer hardware, it is an era that can be realistically expressed not only in movie visual effects but also in console games. In the production of such realistic 3D models, 3D scans are increasingly used because they can obtain hyper-realistic results with relatively little effort. Among the various 3D scanning methods, photogrammetry can be used only with a camera. Therefore, no additional hardware is required, so its demand is rapidly increasing. Most 3D artists shoot as many images as possible with a video camera, etc., and then calculate using all of those images. Therefore, the photogrammetry method is recognized as a task that requires a lot of memory and long hardware operation. However, research on how to obtain precise results with 3D photogrammetry scans is insufficient, and a large number of photos is being utilized, which leads to increased production time and data capacity and decreased productivity. In this study, point cloud data generated according to changes in the number and resolution of photographic images were produced, and an experiment was conducted to compare them with original data. Then, the precision was measured using the average distance value and standard deviation of each vertex of the point cloud. By comparing and analyzing the difference in the precision of the 3D photogrammetry scans according to the number and resolution of images, this paper presents a direction for obtaining the most precise and effective results to 3D artists.

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References

  1. G. Tucci, G. Guidi, D. Ostuni, F. Costantino, M. Pieraccini, and J.-A. Beraldin, "Photogrammetry and 3D Scanning: Assessment of Metric Accuracy for the Digital Model of Danatello's Maddalena," Proceedings of the 2001 Workshop of Italy-Canada on 3D Digital Imaging and Modeling Application of: Heritage, Industry, Medicine, and Land,Padova, April 2001.
  2. Galantucci, Luigi & Lavecchia, Fulvio & Percoco, Gianluca & Raspatelli, Sergio, "New method to calibrate and validate a high-resolution 3D scanner based on photogrammetry," Precision Engineering, Volume 38, Issue 2, pp. 279-291, April 2014. DOI:https://doi.org/10.1016/j.precisioneng.2013.10.002
  3. Rachel Opitz, Katie Simon, Adam Barnes, Kevin Fisher, Lauren Lippiello, "Close-range photogrammetry vs. 3D scanning: Comparing data capture," processing and model generation in the field and the lab. The Computer Applications and Quantitative Methods in Archaeology (CAA) 2012 Conference, 2012.
  4. Percoco, G., Guerra, M.G., Sanchez Salmeron, A.J, "Experimental investigation on camera calibration for 3D photogrammetric scanning of micro-features for micrometric resolution," Int J Adv Manuf Technol 91, pp. 2935-2947, August 2017. DOI:https://doi.org/10.1007/s00170-016-9949-6
  5. J. Hafeez, S. Lee, S. Kwon, and A. Hamacher, "Image Based 3D Reconstruction of Texture-less Objects for VR Contents," International journal of advanced smart convergence, vol. 6, no. 1, pp. 9-17, Mar. 2017. DOI:10.7236/IJASC.2017.6.1.9.
  6. J. Choi, S. Kwon, K. Son, and J. Yoo, "Fast key-frame extraction for 3D reconstruction from a handheld video," International journal of advanced smart convergence, vol. 5, no. 4, pp. 1-9, Dec. 2016. DOI: https://doi.org/10.7236/IJASC.2016.5.4.1
  7. G. Lee, P. Choi, J. Nam, H. Han, S. Lee, and S. Kwon, "A Study on the Performance Comparison of 3D File Formats on the Web," International journal of advanced smart convergence, vol. 8, no. 1, pp. 65-74, Mar. 2019. DOI: http://dx.doi.org/10.7236/IJASC.2019.8.1.65
  8. L. Hwang, J. Lee, J. Hafeez, J. Kang, S. Lee, and S. Kwon, "A Study on Optimized Mapping Environment for Real-time Spatial Mapping of HoloLens," International Journal of Internet, Broadcasting and Communication, vol. 9, no. 3, pp. 1-8, Aug. 2017. DOI:http://dx.doi.org/10.7236/IJIBC.2017.9.3.1
  9. S. C. Kwon, H. B. Chae, S. J. Lee, K. C. Son, and S. H. Lee, "A Study on Depth Information Acquisition Improved by Gradual Pixel Bundling Method at TOF Image Sensor," International Journal of Internet, Broadcasting and Communication, vol. 7, no. 1, pp. 15-19, Feb. 2015. DOI:http://dx.doi.org/10.7236/IJIBC.2015.7.1.15
  10. Wiora, "Optical 3D Metrology," Universitatsbibliothek Heidelberg, pp. 36, 2006. DOI: https://doi.org/10.11588/heidok.00001808
  11. Forest Collado J, "New Methods for Triangulation Based Shape Acquisition using Laser Scanners," Thesis, Universitat de Girona, 2004.
  12. L.H Kim, "A Study of a Photogrammetry Scanning Quality Based on a High Dynamic Range Image," Thesis, Kwangwoon University, pp. 1-95, 2019.
  13. H. Kamel, Youssef Chahir, Mohamed Khireddine Kholladi, "SIFT Detectors for Matching Aerial Images in Reduced Space," IEEE International Conference on Computer Integrated Manufacturing - CIP'2007, 2007, Setif, Algeria. pp. 10
  14. Richard Hartley and Andrew Zisserman, "Multiple View Geometry in Computer Vision," Cambridge University Press. pp. 155-157, 2003.
  15. Matthew Berger, Andrea Tagliasacchi, Lee Seversky, Pierre Alliez, Gael Guennebaud, "A Survey of Surface Reconstruction from Point Clouds," Computer Graphics Forum, Wiley, pp. 27, 2016 DOI: https://onlinelibrary.wiley.com/doi/10.1111/cgf.12802
  16. Eberhard L.A, Sirguey P, Miller A, Marty M, Schindler K, Stoffel A, Buhler Y, "Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping," The Cryosphere, pp. 69-94, 2021 DOI:https://doi.org/10.5194/tc-15-69-2021
  17. Grisetti G, Grzonka S, Stachniss C, Pfaff P, Burgard W, "Efficient estimation of accurate maximum likelihood maps in 3D," International Conference on Intelligent Robots and Systems, pp.3472-3478, 2017 DOI: https://ieeexplore.ieee.org/document/4399030