Enhancement Method of Depth Accuracy in DIBR-Based Multiview Image Generation

다시점 영상 생성을 위한 DIBR 기반의 깊이 정확도 향상 방법

  • 김민영 ((주)유윈인포시스 기술연구소) ;
  • 조용주 (상명대학교 미디어소프트웨어학과) ;
  • 박경신 (단국대학교 응용컴퓨터공학과)
  • Received : 2016.08.09
  • Accepted : 2016.08.29
  • Published : 2016.09.30


DIBR (Depth Image Based Rendering) is a multimedia technology that generates the virtual multi-view images using a color image and a depth image, and it is used for creating glasses-less 3-dimensional display contents. This research describes the effect of depth accuracy about the objective quality of DIBR-based multi-view images. It first evaluated the minimum depth quantization bit that enables the minimum distortion so that people cannot recognize the quality degradation. It then presented the comparative analysis of non-uniform domain-division quantization versus regular linear quantization to find out how effectively express the accuracy of the depth information in same quantization levels according to scene properties.

DIBR (Depth Image Based Rendering)은 동일 시점의 색상 영상과 깊이 영상을 참조해서 임의 개수의 중간 시점 영상을 생성하는 기법으로 무안경식 다시점 입체 디스플레이를 위한 콘텐츠 제작에 활용할 수 있다. 본 연구에서는 DIBR 기법을 사용해서 생성되는 다시점 중간 영상의 객관적 품질에 깊이 정확도가 미치는 영향에 대해 설명한다. 본 연구는 먼저 사람이 인지할 수 없는 범위에서 왜곡을 보장하기 위한 최소 깊이 양자화 계수를 도출한다. 그리고 장면 구성의 특성에 따라 같은 양자화 수준에서 깊이 정보의 정확도를 효과적으로 표현하기 위한 비균등 영역분할 양자화 방법을 선형 양자화와 비교 분석한 결과를 제시한다.



  1. D. Lanman, M. Hirsch, Y. Kim, and R. Raskar, "Content- Adaptive Parallax Barriers: Optimizing Dual-Layer 3D Displays using Low-Rank Light Field Factorization," in Proceedings of ACM SIGGRAPH Asia 2010 papers (SIGGRAPH ASIA '10), ACM, Vol.29, Issue 6, Article No.163, December, 2010.
  2. A. J. Woods and J. Helliwell, "Investigating the cross compatibility of IR‐controlled active shutter glasses," in Proc. of SPIE Stereoscopic Displays and Applications XXIII, 8288(1C), pp.1-10, 2012.
  3. KOCCA, "New breakthrough of the 3D TV markget: 'Glasses-free 3D' technology," 3D/CG Issue Report, 2012.
  4. "Digital Multimedia Broadcasting (DMB) Video-Associated Stereoscopic Data Service," Standard No. TTAK.KO-07.0064, 2008.
  5. J. I. Jung and Y. S. Ho, "Color Correction Algorithm Based on Camera Characteristics for Multi-view Video Coding," Signal, Image, and Video Processing, 2012, 11760-012-0341.
  6. K. Choi and Y. Seo, "Efficient Multi-Camera Calibration System," Korean Institute Of Information Technology, Vol.9, No.7, pp.215-223, 2011.
  7. C. Fehn, "Depth-Image-Based Rendering (DIBR), Compression and Transmission for a New Approach on 3D-TV," Proc. SPIE Stereoscopic Display and Virtual Reality Systems XI, Vol.5291, pp.93-104, 2004.
  8. C. Fehn, "A 3D-TV Approach Using Depth-Image-Based Rendering (DIBR)," in Proc. of Visualization, Imaging, and Image Processing, pp.482-487, 2003.
  9. N. Hur, H. L. Lee, G. S. Lee, S. J. Lee, A. Gotchev, and S. I. Park, "3DTV Broadcasting and Distribution Systems," IEEE Transactions on Broadcasting, Vol.57, No.2, pp.395-407 2011.
  10. A. Redert, M. O. de Beeck, and C. Fehn, "ATTEST: Advanced Three-dimensional Television System Technologies," 3D Data Processing Visualization and Transmission, pp.313-319, 2002.
  11. M. Kim and Y. Cho, "Design and Implementation of DIBR-based Multi-view Image Generation Simulation System," Journal of Korean Institute of Information Technology, Vol.10, No.8, pp.189-198, 2012.
  12. L. Do, S. Zinger, Y. Morvan, and P. H. N. de With, "Quality Improving Techniques for Free-Viewpoint DIBR," in Proc. of IEEE 3D-TV CON'09, pp.1-4, 2009.
  13. L. Zhang and W. J. Tam, "Stereoscopic Image Generation Based on Depth Images for 3D TV," Proc. IEEE Trans. on In Broadcasting, Vol.51, No.2, pp.191-199, 2005.
  14. M. Magnor, P. Eisert, and B. Girod, "Multi-View Image Coding with Depth Maps and 3-D Geometry for Prediction," in Proc. of SPIE: Visual Communications and Image Processing, pp.263-271, 2001.
  15. S. B. Lee, K. J. Oh, and Y. S. Ho, "Segment-based Multiview Depth Map Estimation Using Belief Propagation From Dense Multi-view Video," in Proc. of IEEE, 3DTV Conference: The True Vision-Capture, Transmission and Display of 3D Video, pp.193-196, 2008.
  16. J. Lee and C. Kim, "Stereoscopic Image Generation with Optimal Disparity using Depth Map Preprocessing and Depth Information Analysis," Proc. The Korean Society of Broadcast Engineers Journal of Broadcast Engineering, Vol.14, No.2, pp.164-177, 2009.
  17. G. M. Um, F. Speranza, L. Zhang, W. J. Tam, R. Renaud, L. B. Stelmach, and C. H. Ahn, "Investigation on the Effect of Disparity-Based Asymmetrical Filtering of Stereoscopic Video," in Proc. SPIE 5150, Visual Communications and Image Processing 2003, pp.110-118, 2003.
  18. W. J. Tam, G. Alain, L. Zhang, T. Martin, and R. Renaud, "Smoothing depth maps for improved stereoscopic image quality," in Proceedings of SPIE Conf. Three-Dimensional TV, Video, and Display III, Philadelphia, PA, 5599, pp.162-172, 2004.
  19. K. J. Oh and Y. S. Ho, "Non-linear Bi-directional Prediction for Depth Coding," Advances in Multimedia Information Processing - PCM 2009, Vol.5879, pp.522-531, 2009.
  20. X. Ye, J. Yang, H. Huang, and C. Hou, "Computational Multi-View Imaging with Kinect," IEEE Transactions on Broadcasting, Vol.60, No.3, pp.540-554, 2014.
  21. G. Lee and J. Yoo, "Real-time Virtual-viewpoint Image Synthesis Algorithm Using Kinect Camera," Journal of Electrical Engineering & Technology, Vol.9, No.3, pp.742-748, 2014.
  22. Q. H. Nguyen, M. N. Do, and S. J. Patel, "Depth Image-Based Rendering with Low Resolution Depth," Proc. IEEE, the 2nd ICIP, pp.553-556, 2009.
  23. Q. Yang, R. Yang, J. Davis, and D. Nister, "Spatial-Depth Super Resolution for Range Images," Proc. IEEE CVPR'07, pp.1-8, 2007.
  24. W. Jang and Y. Ho, "Hybrid disparity map generation method based on reliability," Proceedings of the Korean Society of Broadcast Engineers Conference, Vol.2015, No.7, pp.73-74, 2015.
  25. J. Diebel and S. Thrun, "An application of markov random fields to range sensing," Advances in Neural Information Processing Systems, Vol.18, pp.291-298, 2006.
  26. G. Leon, H. Kalva, and B. Furht, "3D Video Quality Evaluation with Depth Quality Variations," in Proc. of IEEE 3DTV Conference, pp.301-304, 2009.
  27. T. Kim, J. H. Kim, M. W. Park, and J. Shin, "Hybrid Down-Sampling Method of Depth Map Based on Moving Objects," The Journal of the KICS, Vol.37A, No.11, pp.918-926, 2012.
  28. J. H. Jung, J. Yeom, J. Hong, K. Hong, S. W. Min, and B. Lee, "Effect of fundamental depth resolution and cardboard effect to perceived depth resolution on multi-view display," OSA, Optics Express, Vol.19, No.21, pp.20468-20482, 2011.
  29. S. Zinger, L. Do, and P. H. N. de With, "Free-viewpoint depth image based rendering," Journal of Visual Communication and Image Representation, Vol.21, No.5-6, pp.533-541, 2010.
  30. K. J. Oh, S. Yea, and Y. S. Ho, "Hole-Filling Method Using Depth Based In-Painting for View Synthesis in Free Viewpoint Television (FTV) and 3D Video," in Proc. of 27th Conference on Picture Coding Symposium, pp.233-236, 2009.
  31. M. Kim, Y. Cho, H. G. Choo, J. Kim, and K. S. Park, "Effects of Depth Map Quantization for Computer-Generated Multiview Images using Depth Image-Based Rendering," KSII Transactions of Internet and Information Systems, Vol.5, No.11, pp.2175-2190, 2011.
  32. H. Kim, J. Jung, J. Lee, H. Kang, K. Dong, and W. Chung, "Picture Quality According to the Type of Detector in Full-field Digital Mammography," Journal of the Korean Physical Society, Vol.58, No.2, pp.364-371, 2011.
  33. I. Ideses, L. Yaroslavsky, I. Amit, and B. Fishbain, "Depth Map Quantization - How much is sufficient?" in Proc. of IEEE 3DTV Conference, pp.1-4, 2007.
  34. C. Yun, S. Ko, and G. Lee, "The Study about the Differential compression based on the ROI(Region Of Interest)," Journal of the Korea Institute of Information and Communication Engineering, Vol.18, No.3, pp.679-686, 2014.
  35. S. P. Lloyd, "Least Squared Quantization in PCM," IEEE Trans. Information Theory, Vol.28, No.2, pp.129-137, 1982.
  36. OpenGL FAQ, The Depth Buffer: 12.07012.070 Why is there more precision at the front of the depth buffer? [Internet],