JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Efficient Depth Map Generation for Various Stereo Camera Arrangements
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Efficient Depth Map Generation for Various Stereo Camera Arrangements
Jang, Woo-Seok; Lee, Cheon; Ho, Yo-Sung;
  PDF(new window)
 Abstract
In this paper, we propose a direct depth map acquisition method for the convergence camera array as well as the parallel camera array. The conventional methods perform image rectification to reduce complexity and improve accuarcy. However, image rectification may lead to unwanted consequences for the convergence camera array. Thus, the proposed method excludes image rectification and directly extracts depth values using the epipolar constraint. In order to acquire a more accurate depth map, occlusion detection and handling processes are added. Reasonable depth values are assigned to the obtained occlusion region by the distance and color differences from neighboring pixels. Experimental results show that the proposed method has fewer limitations than the conventional methods and generates more accurate depth maps stably.
 Keywords
epipolar constraint;image rectification;occlusion handling;stereo matching;
 Language
Korean
 Cited by
1.
3차원 합성영상의 화질 개선을 위한 깊이 경계 선명화,송윤석;이천;호요성;

한국통신학회논문지, 2012. vol.37A. 9, pp.786-791 crossref(new window)
2.
U-시차 지도와 정/역방향 에러 제거를 통한 자동차 환경에서의 모션 필드 예측,서승우;이규철;이상용;유지상;

한국통신학회논문지, 2015. vol.40. 12, pp.2343-2352 crossref(new window)
3.
조명 변화에 강인한 상호 정보량 기반 스테레오 정합 기법,허용석;

한국통신학회논문지, 2015. vol.40. 11, pp.2271-2283 crossref(new window)
 References
1.
L. Zhang and W.J. Tam, "Stereoscopic image generation based on depth images for 3DTV," IEEE Trans. Broadcast., vol. 51, no. 2, pp. 191-199, June 2005. crossref(new window)

2.
S.Y. Kim, J.H. Cho, and A. Koschan, "3D video generation and service based on a TOF depth sensor in MPEG-4 multimedia framework," IEEE Trans. Consum. Electron., vol. 56, no. 3, pp. 1730-1738, Aug. 2010. crossref(new window)

3.
W.S. Jang, Y.S. Ho, "Efficient Disparity Map Estimation Using Occlusion Handling for Various 3D Multimedia Applications," IEEE Trans. Consum. Electron., vol. 57, no. 4, pp. 1937-1943, Nov. 2011. crossref(new window)

4.
D. Sharstein and R. Szeliski, "A taxonomy and evaluation of dense two-frame stereo correspondence algorithms," IEEE Workshop on Stereo and Multi-Baseline Vision, pp. 131-140, 2001.

5.
Y.S. Kang and Y.S. Ho, "An Efficient Image Rectification Method for Parallel Multi-Camera Arrangement," IEEE Trans. Consum. Electron., vol. 57, no. 3, pp. 1041-1048, Aug. 2011. crossref(new window)

6.
S.Z. Li, Markov Random Field Modeling in Image Analyysis, 2nd ed. New York: Springer-Verlag, 2001.

7.
C. Lee and Y.S. Ho, "Boundary filtering on synthesized views of 3D video," International Symposium on Signal Processing, Image Processing and Pattern Recognition, pp. 15-18, 2008.

8.
Q. Yang, L. Wang, and N. Ahuja, "A constant-space belief propagation algorithm for stereo matching," IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1458-1465, 2010.

9.
Q. Yang, C. Engels, and A. Akbarzadeh. "Near real-time stereo for weakly-textured scenes," British Machine Vision Conference, pp. 80-87, 2008.