Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
권호 표지
DOI QR코드

DOI QR Code

Method for Determining Variable-Block Size of Depth Picture for Plane Coding

깊이 화면의 평면 부호화를 위한 가변 블록 크기 결정 방법

  • 권순각 (동의대학교 컴퓨터소프트웨어공학과) ;
  • 이동석 (동의대학교 컴퓨터소프트웨어공학과)
  • Received : 2017.06.23
  • Accepted : 2017.06.27
  • Published : 2017.07.03
Download PDF
⟨ Previous Next ⟩

Abstract

The Depth Picture can be Encoded by the Plane Coding Mode that is the Method for Coding Mode by Considering a Part of the Picture as the Plane. In this Paper, we Propose the Method of Determining the Variable-sized Block for Variable Block Coding in the Plane Coding Mode for the Depth Picture. The Depth Picture Can be Encoded in the Plane Coding Through Estimating the Plane Which is Close to Pixels in the Block Using Depth Information. The Variable-sized Block Coding in the Plane Coding can be Applied as Follows. It Calculates the Prediction Error between Predicted Depths by the Plane Estimation and the Measured Depths. If Prediction Error is Below the Threshold, the Block is Encoded by Current Size. Otherwise, it Divides the Block and Repeats Above. If the Block is Divided Below the Minimum Size, the Block is not Encoded by the Plane Coding Mode. The Result of the Simulation of the Proposed Method Shows that the Number of Encoded Block is Reduced to 19% as Compared with the Method Using the Fixed-sized Block in the Depth Picture Composed of one Plane.

깊이 화면을 부호화함에 있어서 깊이 화면의 일부를 평면으로 추정하여 부호화하는 평면 부호화 모드를 적용할 수 있다. 본 논문에서는 평면 부호화 모드를 통한 깊이 영상 부호화에서 가변 블록 부호화를 위해 가변 블록 크기를 결정하는 방법을 제안한다. 깊이를 통해 블록 내 화소에 대해 제일 근접한 평면을 추정하는 방법을 통해 평면 부호화를 수행할 수 있다. 평면 부호화를 수행할 때, 가변 블록 부호화를 다음과 같이 적용할 수 있다. 먼저 최대 블록 크기에 대하여 추정 오차를 계산한 뒤 오차가 임계값 이하라면 해당 블록 크기가 선택 된다. 반면 오차가 임계값을 초과한다면 해당 블록이 분할되고 위 과정을 반복한다. 분할된 블록 크기가 최소 블록 크기 미만이 되면 해당 블록은 평면 부호화 모드로 선택되지 않는다. 제안된 방법을 실험한 결과, 부호화하여야 할 블록의 개수가 평면으로 이루어진 영상에서 고정 블록 크기를 이용한 방법에 비해 19%로 줄었다.

Keywords

References

  1. Lee D. S. and Kwon S. K., "A Recognition Method for Moving Objects Using Depth and Color Information," Journal of Korea Multimedia Society, Vol. 19, No. 4, 2016, pp. 681-688. https://doi.org/10.9717/kmms.2016.19.4.681
  2. Kwon S. K and Lee D. S. "Soon-Kak Kwon, Dong-Seok Lee. (2015). Correction of Perspective Distortion Image Using Depth Information," Journal of Korea Multimedia Society, Vol. 18, No. 2, 2015, pp. 106-112. https://doi.org/10.9717/kmms.2015.18.2.106
  3. Preis J., Kessel M., Werner M., and Linnhoff-Popien C. L., "Gait Recognition with Kinect," Proceeding of the First Workshop on Kinect in Pervasive Computing, 2012, pp. P1-P4.
  4. Salinas R. M., Medina-Carnicer R., Madrid-Cuevas F. J., and Carmona-Poyato A., "Depth Silhouettes for Gesture Recognition," Pattern Recognition Letters, Vol. 29, No. 3, 2008, pp. 319-329. https://doi.org/10.1016/j.patrec.2007.10.011
  5. 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.
  6. 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
  7. 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
  8. Oh K. J., Vetro A., and Ho Y. S., "Depth Coding Using a Boundary Reconstruction Filter for 3-D Video Systems," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 21, No. 3, 2011, pp. 350-359. https://doi.org/10.1109/TCSVT.2011.2116590
  9. Jäger F., "Simplified Depth Map Intra Coding with An Optional Depth Lookup Table," Proceeding of 2012 International Conference on 3D Imaging, 2012, pp. 1-4.
  10. 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
  11. 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
  12. 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, 2011, pp. 1155-1163. https://doi.org/10.6109/jkiice.2011.15.5.1155
  13. 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, 2016, pp. 11-17. https://doi.org/10.9723/jksiis.2016.21.5.011
  14. Kwon S. K., Lee D. S., and Park Y. H., "Depth Video Coding Method for Spherical Object," Journal of Korea Multimedia Society, Vol. 19, No. 10, 2016. pp. 23-29.
  15. Kwon S. K., Tamhankar A., and Rao K. R., "Overview of H.264/MPEG-4 Part 10," Journal of Visual Communications and Image Representation, Vol. 17, No. 2, 2006. pp. 186-216. https://doi.org/10.1016/j.jvcir.2005.05.010
  16. Sullivan J. and Han W. J., "Overview of the High Efficiency Video Coding (HEVC) Standard," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 22, No. 12, 2012, pp. 1649-1668. https://doi.org/10.1109/TCSVT.2012.2221191
  17. Fu C. H., Chan Y. L., and Siu W. C., "Fast Motion Estimation and Mode Decision for H.264 Reverse Transcoding," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 42, No. 24, 2006, pp. 1685-1386.
  18. Yin P. and Jill B., "Fast Mode Decision and Motion Estimation for H.264," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, No. 2, 2003, pp. 1246-1249.
  19. Wang X., Sun J., and Zheng S., "Variable Block Size Selection for a Transcoder Based on MB Movement Information," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 17, No. 2, 2008, pp. 177-180.
  20. Lin J. L., Chen Y. W., and Huang Y. W., "Motion Vector Coding in the HEVC Standard," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 7, No. 6, 2013, pp. 957-968.
  21. Kwon S. K. and Jang W. S., "Zoom Motion Estimation Method Using Variable Block-Size," Journal Of Broadcast Engineering, Vol. 19, No. 6, 2014, pp. 916-924. https://doi.org/10.5909/JBE.2014.19.6.916
  22. Hartley R. and Zisserman A., "Multiple View Geometry in Computer Vision," Cambridge University Press, Cambridge, UK, 2008.
  23. 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.
  24. 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