MATEC Web Conf.
Volume 232, 20182018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|Number of page(s)||4|
|Section||3D Images Reconstruction and Virtual System|
|Published online||19 November 2018|
- H. Shao, The Opportunities and Challenges Faced by the Development of 3D Films in China, Contemp. Cinema 6, 175-178 (2017) [Google Scholar]
- L. Zhu, Deep vision principle and stereo image characteristics of the human eye, J. B. Film. Aca 4, 130-137 (2016) [Google Scholar]
- D. Scharstein and R. Szeliski, A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision, 131-140 (2001). [CrossRef] [Google Scholar]
- K. Konda and R. Memisevic, Unsupervised learning of depth and motion, Comput. Sci. (2013) [Google Scholar]
- K. Karsch, C. Liu, S. B. Kang, and N. England, Depth extraction from video using nonparametric sampling, TPAMI (2014) [Google Scholar]
- C. Liu, J. Yuen, A. Torralba, J. Sivic, and W. Freeman, Sift flow: dense correspondence across difference scenes, (2008) [Google Scholar]
- D. Eigen, C. Puhrsch, R. Fergus, Depth map prediction from a single image using a multi-scale deep network, Proceedings of the Advances in Neural Information Processing Systems, 2366-2374 (2014) [Google Scholar]
- A. Krizhevsky, I. Sutskever and G. E. Hinton, Imagenet classfication with deep convlutional neural networks, International Conference on Neural Information Processing Systems, 2643-2651 (2013) [Google Scholar]
- F. H. Sinz, J. Q. Candela, G. H. Bakır, C. E, Rasmussen, and M. O. Franz, Learning depth from stereo, 45-252 (2004) [Google Scholar]
- Z. W. Liu, P. An, Z. Y. Zhang, Depth Image Based Rendering, 466-471 (2007) [Google Scholar]
- Y. C. Fan, Y. C. Chen, S. Y. Chou, Vivid-DIBR Based 2D-3D Image Conversion System for 3D Display, J. Display. Technol 10, 892-898 (2014) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.