Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
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Depth Video Coding Method for Spherical Object

구형 객체의 깊이 영상 부호화 방법

  • 권순각 (동의대학교 컴퓨터소프트웨어공학과) ;
  • 이동석 (동의대학교 컴퓨터소프트웨어공학과) ;
  • 박유현 (동의대학교 컴퓨터소프트웨어공학과)
  • Received : 2016.12.06
  • Accepted : 2016.12.14
  • Published : 2016.12.30
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Abstract

In this paper, we propose a method of depth video coding to find the closest sphere through the depth information when the spherical object is captured. We find the closest sphere to the captured spherical object using method of least squares in each block. Then, we estimate the depth value through the found sphere and encode the depth video through difference between the measured depth values and the estimated depth values. Also, we encode factors of the estimated sphere with encoded pixels within the block. The proposed method improves the coding efficiency up to 81% compared to the conventional DPCM method.

본 논문은 구형 객체가 촬영된 깊이 영상에서 깊이 정보를 통하여 제일 근접한 구를 찾아내어 깊이 영상을 부호화하는 방법을 제안한다. 블록단위로 분할된 깊이 영상에 대해 최소자승법을 통해 촬영된 구형 객체와 제일 근접한 구의 형태를 찾는다. 그 후 찾아낸 구의 형태로 깊이 값을 예측하고, 측정된 깊이 값과의 오차를 통해 깊이 영상을 부호화한다. 또한, 블록 내의 부호화된 각 깊이 화소들과 찾아낸 구의 인자 정보를 같이 부호화한다. 제안된 방법으로 구형 객체에 대해 기존 DPCM 방법보다 최대 81% 이상의 부호화 효율 향상이 이루어졌다.

Keywords

References

  1. Lee D. S. and Kwon, S. K., “A Rcognition Method for Moving Objects Using Depth and Color Information,” Journal of Korea Multimedia Society, Vol. 19, No. 4, pp. 681-688, 2016. https://doi.org/10.9717/kmms.2016.19.4.681
  2. Preis, J., Kessel, M., Werner, M., and Linnhoff-Popien, C., "Gait Recognition with Kinect," Proceeding of the First Workshop on Kinect in Pervasive Computing, pp. 1-4, 2012.
  3. Kwon S. K. and Lee, D. S., “Correction of Perspective Distortion Image Using Depth Information,” Journal of Korea Multimedia Society, Vol. 18, No. 2, pp. 106-112, 2015. https://doi.org/10.9717/kmms.2015.18.2.106
  4. Lee D. S. and Kwon, S. K., “Improvement of Depth Video Coding by Plane Modeling,” Journal of the Korea Industrial Information Systems Research, Vol. 21, No. 5, pp. 11-17, 2016. https://doi.org/10.9723/jksiis.2016.21.5.011
  5. Lee, D. S. and Kwon, S. K., “Touch Pen Using Depth Information,” Journal of Korea Multimedia Society, Vol. 18, No. 11, pp. 1313-1318, 2015. https://doi.org/10.9717/kmms.2015.18.11.1313
  6. Kwon S. K. and Lee, D. S., "Recognition Method of Multiple Objects for Virtual Touch Using Depth Information," Journal of the Korea Industrial Information Systems Research, Vol. 21, No. 1, 27-34, 2016. https://doi.org/10.9723/jksiis.2016.21.1.027
  7. Lee D. S. and Kwon, S. K., "Video Event Control System by Recognition of Depth Touch," Journal of the Korea Industrial Information Systems Research, Vol. 21, No. 1, 35-42, 2016. https://doi.org/10.9723/JKSIIS.2016.21.1.035
  8. Suryanarayan, P., Subramanian, A., and Mandalapu, D., "Dynamic Hand Pose Recognition Using Depth Data," Proceeding of 20th International Conference on Pattern Recognition, 2010, pp. 3105-3108.
  9. Zollhoefer, M., Martinek, M., Greiner, G., Stamminger, M., and Suessmuth, J., "Automatic Reconstruction of Personalized Avatars from 3D Face Scans," Computer Animation and Virtual Worlds, Vol. 22, No. 2-3, 2011, pp. 195-202. https://doi.org/10.1002/cav.405
  10. Tong, J., Zhou, J., Liu, L., Pan, Z. and Yan, H., "Scanning 3D Full Human Bodies Using Kinects," IEEE Transactions on Visualization and Computer Graphics, Vol. 18, No. 4, 2012, pp. 643-650. https://doi.org/10.1109/TVCG.2012.56
  11. Jager, F., "Simplified Depth Map Intra Coding With an Optional Depth Lookup Table," Proceeding of 2012 International Conference on 3D Imaging, 2012, pp. 1-4.
  12. Liu, S., Lai, P., Tian, D., and Chen, C. W., "New Depth Coding Techniques with Utilization of Corresponding Video," IEEE Transactions on Broadcasting, Vol. 57, No. 2, 2011, pp. 551-561. https://doi.org/10.1109/TBC.2011.2120750
  13. Oh, B. T., Lee, J., and Park, D. S., "Depth Map Coding Based on Synthesized View Distortion Function," IEEE Journal of Selected Topics in Signal Processing, Vol. 5, No. 7, 2011, pp. 1344-1352. https://doi.org/10.1109/JSTSP.2011.2164893
  14. Park S. H. and Yoo, J. S., “Depth Map Pre-Processing Using Gaussian Mixture Model and Mean Shift Filter,” Journal of the Korea Institute of Information and Communication Engineering, Vol. 15, No. 5, pp. 1155-1163, 2011. https://doi.org/10.6109/jkiice.2011.15.5.1155
  15. Kwon S. K. and Lee, D. S., "Obtainment of Background Image Using Depth Information," International Organization of Scientific Research Journal of Engineering, Vol. 5, No. 8, 2015, pp. 43-46.
  16. Kim, S. Y., Yoon, C. Y., and Yu, E. J., "A Study on the Development of Learning Contents of Augmented Reality by Perception Rate and Speeding," The Journal of Internet Electronic Commerce Research, Vol. 14, No. 4, pp. 313-333, 2014.
  17. Kim S. Y. and Lee, S. M., "Implementation of an Image Board Remote Control System Using PDA Based on Embedded Linux in Wireless Internet," The Journal of Information Systems, Vol. 17, No. 1, pp. 155-171, 2008. https://doi.org/10.5859/KAIS.2008.17.1.155

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