DOI QR코드

DOI QR Code

A Multi 3D Objects Augmentation System Using Rubik's Cube

루빅스 큐브를 활용한 다 종류 3차원 객체 증강 시스템

  • Lee, Sang Jun (School of Computer Science and Engineering, Handong Global University) ;
  • Kim, Soo Bin (School of Computer Science and Engineering, Handong Global University) ;
  • Hwang, Sung Soo (School of Computer Science and Engineering, Handong Global University)
  • Received : 2017.07.17
  • Accepted : 2017.07.28
  • Published : 2017.08.31

Abstract

Recently, augmented reality technology has received much attention in many fields. This paper presents an augmented reality system using Rubiks' Cube which can augment various 3D objects depending on patterns of a Rubiks' cube. The system first detects a cube from an image using partitional clustering and strongly connected graph. Thereafter, the system detects the top side of the cube and finds a proper pattern to determine which object should be augmented. An object corresponding to the pattern is finally augmented according to the camera viewpoint. Experimental results show that the proposed system successfully augments various virtual objects in real time.

Keywords

References

  1. Apple, Google, Microsoft-Who is Winning the Augmented Reality War?, http://www.ar-intelligence.info/2017/06/apple-google-microsoft-who-is-winning-the-augmented-reality-wars/ (accessed July, 3, 2017).
  2. Pokemon Go Catches Five New World Records, http://www.guinnessworldrecords.com/news/2016/8/pokemon-go-catches-five-world-records-439327 (accessed July, 3, 2017).
  3. Unity with Native Tango Support and Vuforia Integration Coming Later Thins Year, https://augmented.reality.news/news/unity-with-native-tango-support-vuforia-integration-coming-later-year-0177435/ (accessed July, 3, 2017).
  4. The Perspective-Three-Point Principle, http://iplimage.com/blog/p3p-perspective-point-overview/ (accessed May, 28, 2017).
  5. N. David, "Preemptive RANSAC for Live Structure and Motion Estimation," Machine Vision and Applications, Vol. 16, Issue 5, pp. 321-329, 2005. https://doi.org/10.1007/s00138-005-0006-y
  6. M. Raul, J.M.M. Montiel, and J.D. Tardos, "ORB-SLAM: A Versatile and Accurate Monocular SLAM System," IEEE Transactions on Robotics, Vol. 31, Issue 5, pp. 1147-1163, 2015. https://doi.org/10.1109/TRO.2015.2463671
  7. Y. Lee, and Y. Seo, "Vision-Based SLAM in Augmented/Mixed Reality," Journal of Korea Multimedia Society, Vol. 13, Issue 3, pp. 12-20, 2009.
  8. J. Illingworth and J. Kittler, "The Adaptive Hough Transform," IEEE Transactions on Pattern an Analysis and Machine Intelligence, Vol. 9, Issue 5, pp. 690-698, 1987.
  9. C. John, "A Computational Approach to Edge Detection," IEEE Transactions on Pattern an Analysis and Machine Intelligence, Vol. 8, Issue 6, pp. 679-698, 1986.
  10. P.V.C Hough, Method and Means for Recognizing Complex Patterns, United States, 1962.
  11. D. Kim, C++ API OpenCV Programming: Digital Image Processing by OpenCV, Korea, 2015, Kame, Gyeonggi-do.
  12. T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein, Introduction to Algorithms: Second Edition, The MIT Press and McGraw-Hill, Cambridge, Massachusetts London, 2001.
  13. D.A. Freedman, Statistical Models: Theory and Practice, Cambridge University Press, England, 2009.
  14. R.C, Gonzalez, and R.E. Woods, Digital Image Processing: Third Edition, Pearson Education International, NewJersey, 2010.