Sheared EPI Analysis for Disparity Estimation from Light Fields

Author:

SUZUKI Takahiro1,TAKAHASHI Keita1,FUJII Toshiaki1

Affiliation:

1. Graduate School of Engineering, Nagoya University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference31 articles.

1. [1] D. Scharstein and R. Szeliski, “A taxonomy and evaluation of dense two-frame stereo correspondence algorithms,” International Journal of Computer Vision, vol.47, no.1-3, pp.7-42, 2002.

2. [2] H. Hirschmüller, “Accurate and efficient stereo processing by semi-global matching and mutual information,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.807-814, 2005. 10.1109/cvpr.2005.56

3. [3] H. Hirschmüller and D. Scharstein, “Evaluation of cost functions for stereo matching,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007. 10.1109/cvpr.2007.383248

4. [4] D. Scharstein and C. Pal, “Learning conditional random fields for stereo,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007. 10.1109/cvpr.2007.383191

5. [5] M. Bleyer, C. Rhemann, and C. Rother, “Patchmatch stereo-stereo matching with slanted support windows,” British Machine Vision Conference, pp.1-11, 2011. 10.5244/c.25.14

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