Adaptive Depth Fusion based on Reliability of Depth Cues for 2D-to-3D Video Conversion

2차원 동영상의 3차원 변환을 위한 깊이 단서의 신뢰성 기반 적응적 깊이 융합

  • 한찬희 (한밭대학교 정보통신전문대학원) ;
  • 최해철 (한밭대학교 정보통신전문대학원) ;
  • 이시웅 (한밭대학교 정보통신전문대학원)
  • Received : 2012.08.22
  • Accepted : 2012.11.30
  • Published : 2012.12.28


3D video is regarded as the next generation contents in numerous applications. The 2D-to-3D video conversion technologies are strongly required to resolve a lack of 3D videos during the period of transition to the full ripe 3D video era. In 2D-to-3D conversion methods, after the depth image of each scene in 2D video is estimated, stereoscopic video is synthesized using DIBR (Depth Image Based Rendering) technologies. This paper proposes a novel depth fusion algorithm that integrates multiple depth cues contained in 2D video to generate stereoscopic video. For the proper depth fusion, it is checked whether some cues are reliable or not in current scene. Based on the result of the reliability tests, current scene is classified into one of 4 scene types and scene-adaptive depth fusion is applied to combine those reliable depth cues to generate the final depth information. Simulation results show that each depth cue is reasonably utilized according to scene types and final depth is generated by cues which can effectively represent the current scene.


Supported by : 한국연구재단


  1. 한찬희, 송인환, 이시웅, "세포동영상의 자동분석을 위한 효율적인 세포추적방법", 한국콘텐츠학회논문지, 제11권, 제5호, pp.32-40, 2011.
  2. Y. Matsumoto, H. Terasaki, K. Sugimoto, and T. Arakawa, "Conversion system of monocular image sequence to stereo using motion parallax," Proc. of SPIE, Vol.3012, pp.108-115, 1997.
  3. T. Okino, H. Murata, K. Taima, T. Iinuma, and K. Oketani, "New television with 2D/3D image conversion techniques," Proc. of SPIE, Vol.2653, pp.96-103, 1995.
  4. M. T. Pourazad, P. Nasiopoulos, and R. K. Ward, "An H.264-based Scheme for 2D to 3D Video Conversion," IEEE Transactions on Consumer Electronics, Vol.55, No.2, pp.742-748, 2009(5).
  5. D. Kim, D. Min, and K. Sohn, "A stereoscopic video generation method using stereoscopic display characterization and motion analysis," IEEE Transactions on broadcasting, Vol.54, No.2, pp.188-197, 2008(6).
  6. W. J. Tam, A. S. Yee, J. Ferreira, S. Tariq, and F. Speranza, "Stereoscopic image rendering based on depth maps created from blur and edge information," Proc. of SPIE, Vol.5664, pp.104-115, 2005.
  7. C. C. Cheng, C. T. Li, and L. G. Chen, "A 2D-to-3D Conversion System Using Edge Information," Digest of Technical Papers Interna tional Conference on Consumer Electronics, pp.377-378, 2010.
  8. S. Battiatoa, S. Curtib, M. L. Casciac, M. Tortorac, and E. Scordato, "Depth Map Generation by Image Classification," Proc. of SPIE, Vol.5302, pp.95-104, 2004.
  9. S. Battiato, A. Capra, S. Curti, and M. La Cascia, "3D stereoscopic image pairs by depth-map generation," Second International Symposium on 3D Data Processing, Visualization and Trans mission, pp.124-131, 2004.
  10. C. C. Cheng, C. T. Li, P. S. Huang, T. K. Lin, Y. M. Tsai, and L. G. Chen, "A Block-based 2D-to-3D Conversion System with Bilateral Filter," Digest of Technical Papers International Conference on Consumer Electronics, pp.1-2, 2009.
  11. Y. L. Chang, J. Y. Chang, Y. M. Tsai, C. L. Lee, and L. G. Chen, "Priority Depth Fusion for the 2D-to-3D Conversion System," Proc. of SPIE, Vol.6805, pp.680513.1-680513.8, 2008.
  12. S. F. Tsai, C. C. Cheng, C. T. Li, and L .G. Chen, "A real-time 1080p 2D-to-3D video conversion system," IEEE, Transactions on Consumer Electronics, Vol.57, No.2, pp.915-922, 2011(5).
  13. D. Comaniciu and P. Meer, "Robust Analysis of Feature Spaces: Color Image Segmentation," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp.750-755, 1997.

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