Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
권호 표지
DOI QR코드

DOI QR Code

A Study for Depth-map Generation using Vanishing Point

소실점을 이용한 Depth-map 생성에 관한 연구

  • 김종찬 (순천대학교 컴퓨터과학과) ;
  • 반경진 (순천대학교 컴퓨터과학과) ;
  • 김치용 (동의대학교 영상정보공학과)
  • Received : 2010.11.15
  • Accepted : 2010.12.23
  • Published : 2011.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

Recent augmentation reality demands more realistic multimedia data with the mixture of various media. High-technology for multimedia data which combines existing media data with various media such as audio and video dominates entire media industries. In particular, there is a growing need to serve augmentation reality, 3-dimensional contents and realtime interaction system development which are communication method and visualization tool in Internet. The existing services do not correspond to generate depth value for 3-dimensional space structure recovery which is to form solidity in existing contents. Therefore, it requires research for effective depth-map generation using 2-dimensional video. Complementing shortcomings of existing depth-map generation method using 2-dimensional video, this paper proposes an enhanced depth-map generation method that defines the depth direction in regard to loss location in a video in which none of existing algorithms has defined.

증강현실에서 다양한 미디어의 결합으로 보다 향상된 현실감 있는 멀티미디어 데이터가 요구되고 있다. 기존의 미디어 정보에 텍스트 및 음성과 비디오 등 다양한 미디어를 결합한 멀티미디어 정보에 대한 첨단 기술이 미디어 산업 전반에 주도적인 위치를 점하고 있다. 특히 인터넷에서의 다양한 의사전달 수단 및 시각화에 대한 관심과 가상공간에서의 의사 표현을 위한 실시간 상호작용 시스템 구축 및 3차원 콘텐츠, 증강현실 기술에 대한 서비스 요구가 증가되고 있다. 이러한 서비스들은 기존 콘텐츠에서 입체감 형성을 위한 3차원 공간구조의 복원에 필요한 깊이 값 생성에 어려움이 있다. 그러므로 2차원 영상을 이용하여 효율적인 Depth-map 생성에 관한 연구가 필요하다. 본 논문에서는 2차원 영상을 이용하여 3차원 공간구조 복원에 필요한 Depth-map 생성기법의 단점을 보완하여, 기존 알고리즘에서 정의 되지 않은 영상 내 소실점 위치에 따른 갚아 방향의 정의를 통한 개선된 Depth-map 생성 기법을 제안하였다.

Keywords

References

  1. D. Burschka, G.D. Hager, Z. Dodds, M. Jagersand, D. Cobzas, and K. Yerex, "Recent Methods for Image-Based Modeling and Rendering," IEEE trans. on Virtual Reality, pp.299, Mar, 2003.
  2. K. Sugihara, "Three Principle in Stereo Vision," Robotics, Vol.1, No.4, pp.391-400, 1986.
  3. D. Marr, and T. Poggio, "A Computational Theory of Human Stereo Vision," Proceedings of the Royal Society of London, B204, pp. 301-308, 1979.
  4. D. Schmalstieg, A. Fuhrmann, G Hesina, Z. Szalavari, L. M. Encarnacao, M. Gervautz, and W. Purgathofer, "Augmented Reality: The interface is everywhere," SIGGRAPH course note, No.27, 2001.
  5. S. B. Pollard, J. E. Mayhew, and J. P. Frisby, "PMF: A Stereo Correspondence Algorithm Using a Disparity Gradient Limit," Perception, Vol.14, pp.449-470, 1985. https://doi.org/10.1068/p140449
  6. N. M. Nasrabadi and C. Y. Chooju "Hop Field Network for Stereo Vision Correspondence," IEEE Trans, on Neural Network, Vol.3, No. 1, Jan. 1992.
  7. D. M. Song, "Conies-Based Stereo, Motion Estimation, and Pose Determination," International Journal of Computer Vision, Vol.10, No.1, pp.7-25, 1993. https://doi.org/10.1007/BF01440844
  8. D. Marr and T. Poggio, "Cooperative Computation of Stereo Disparity," Science, Vol.194, pp.283-287, 1976. https://doi.org/10.1126/science.968482
  9. W. Eric, and L. Grimson, "Computational Experiments with a Feature Based Stereo Algorithm," IEEE Trans. on Pattern Analysis Machine Intelligence Vol.7, No.1, pp.17-34, 1985.
  10. J. P. Frisby, and S. B. Pollard, "Computational Issues in Solving The Stereo Correspondence Problem," Computational Models of Visual Processing, Part 7, Ch.22, pp.331-357, 1990.
  11. A. Saxena, S. H. Chung, and Y. N. Andrew, "Learning Depth from Single Monocular Images," Proc. 19th Ann. Conf. Neural Information Processing Systems, Vol.18, 2005.
  12. T. Hassner and R. Basri, "Example Based 3D Reconstruction from Single 2D Images," Conf. CVPRW '06, pp.15-15, June, 2006.
  13. A. Saxena, S. H. Chung, and Y. N. Andrew, "3D Depth Reconstruction from a Single Still Image," Int J Compute Vis 76, pp.53-69, 2008.
  14. A. Saxena, S. H. Chung, and Y. N. Andrew, "Learning 3D Scene Structure from a Single Still Image," IEEE Trans. on Pattern Analysis Machine Intelligence, Vol.31, No.5, pp.824-840, May, 2009. https://doi.org/10.1109/TPAMI.2008.132
  15. D. S. Kalivas, A. A, Sawchuk, "A Region Matching motion estimation algorithm," CVGIP: Image Understanding, Vol.54, No.2, pp. 275-288, 1991. https://doi.org/10.1016/1049-9660(91)90068-Z
  16. C. Rother, "A New Approach for Vanishing Point Detection in Architectural Environments," Image and Vision Computing 2002, Vol.20, pp.647-655, Aug, 2002. https://doi.org/10.1016/S0262-8856(02)00054-9
  17. S, B, Marapane, and M. M, Trivedi, "Multi- Primitive Hierarchical(MPH) Stereo Analysis," IEEE Trans. on Pattern Analysis Machine Intelligence. Vol.16，No.3, pp.227-240, 1994. https://doi.org/10.1109/34.276122
  18. J. Kogecka, and W. Zhang, "Efficient Computation of Vanishing Points," ICRA 2002, Vol. 1, pp.223-228, 2002.
  19. J. A. Shufelt, "Performance Evaluation and Analysis of Vanishing Point Detection Techniques," Proc. ARPA Image Understanding Workshop, pp.1,113-1,132, Feb.1996.
  20. K. J. Ban, J. C. Kim and E. K. Kim, "An Object Representation System Using Virtual Space Coordinates," KIMICS, Vol.8, No.4, Aug, 2010.
  21. S. Battiato, S. Curti, M. La Cascia, E. Scordato, and M. Tortora, "Depth-Map Generation by Image Classification," In Proceedings of SPIE Electronic Imaging 2004, Three-Dimensional Image Capture and Applications VI, Vol.5302-13, San Jose, California, USA, January 2004.

Cited by

  1. Invisible formative elements at poster layout - Focused on character-driven movie poster - vol.36, pp.None, 2011, https://doi.org/10.21326/ksdt.2012..36.002