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Structures Stereo Camera based Twin Camera Module System

Published: 04 November 2021 Publication History

Abstract

In this paper, we wanted to implement a twin camera module system that is easy to carry and easy to produce 3D content. The proposed twin camera module system is a system that can convert images entered from 2D stereo cameras and output them into three-dimensional images. For the performance evaluation of the system proposed in this paper, the calibration of the rotation and tilt according to the time difference between left and right images of stereo stereoscopic images taken with two lenses, left and right, was evaluated using the Test Platform. In addition, using the Scale Invariant Feature Transform (SIFT) algorithm, we wanted to verify the efficiency of the twin camera module system by verifying the 3D stereoscopic image distance error. The twin-camera module system proposed in this paper can be displayed to the output devices according to different 3D stereoscopic image production methods if the filmed image is changed to 3D stereoscopic image and prepared image and output outside. In addition, it is expected that the prepared images and stereoscopic images will be printed through different channels so that they can be easily applied to many products and easily used to produce 3D stereoscopic video contents.

References

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Shai Avidan and Amnon Shashua. 2000. Trajectory triangulation: 3D reconstruction of moving points from a monocular image sequence. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 4 (April 2000), 348–357. https://doi.org/10.1109/34.845377
[2]
Oh-Young Kwon and Kyoung-Taek Seo. 2015. 3D Reconstruction Using a Single Camera. Journal of the korea Institute of Information and Communication Engineering 19, 12 (Dec. 2015), 2943–2948. https://doi.org/10.6109/jkiice.2015.19.12.2943
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Jongsub Park, June Seok Hong, and Wooju Kim. 2017. A Study on Intuitive IoT Interface System using 3D Depth Camera. Journal of Society for e-Business Studies 22, 2 (May 2017), 137–152. https://doi.org/10.7838/jsebs.2017.22.2.137
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Aviv Yuniar Rahman, Surya Sumpeno, and Mauridhi Hery Purnomo. 2017. Arca detection and matching using Scale Invariant Feature Transform (SIFT) method of stereo camera. 2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT) (Jan. 2017), 66–71. https://doi.org/10.1109/ICSIIT.2017.45
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Seon-Min Rhee, Jong-Moo Choi, and Soo-Mi Choi. 2010. A Method for Reproducing Stereo Images to Adjust Screen Parallax on a 3D Display. Journal of the Korea computer graphics society 16, 4 (2010), 1–10. https://doi.org/10.15701/kcgs.2010.16.4.1
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Torsten Sattler, Bastian Leibe, and Leif Kobbelt. 2016. Efficient & effective prioritized matching for large-scale image-based localization. IEEE transactions on pattern analysis and machine intelligence 39, 9 (Sept. 2016), 1744–1756. https://doi.org/10.1109/TPAMI.2016.2611662

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      cover image ACM Other conferences
      SMA 2020: The 9th International Conference on Smart Media and Applications
      September 2020
      491 pages
      ISBN:9781450389259
      DOI:10.1145/3426020
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 04 November 2021

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      Author Tags

      1. 3D calibration
      2. Camera module
      3. Depth range
      4. SIFT algorithm
      5. Stereo camera
      6. Stereoscopic

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      • Short-paper
      • Research
      • Refereed limited

      Funding Sources

      • This research was supported by the MISP(Ministry of Science, ICT & Future Planning), Korea, under the National Program for Excellence in SW(2017-0-00137) supervised by the IITP(Institute of Information & communications Technology Planing & Evaluation)

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