A Global Nearest-Neighbour Depth Learning Based Automatic 2D to 3D image and Video Conversion
Journal Title: International Journal of Electronics Communication and Computer Technology - Year 2014, Vol 4, Issue 4
Abstract
Despite a significant growth in the last few years, the availability of 3D content is still dwarfed by that of its 2D counterpart. In order to close this gap, many 2D-to-3D image and video conversion methods have been proposed. Methods involving human operators have been most successful but also time-consuming and costly. Automatic methods, that typically make use of a deterministic 3D scene model, have not yet achieved the same level of quality for they rely on assumptions that are often violated in practice. The proposed work is to present a new method based on the radically different approach of learning the 2D-to-3D conversion from examples. It is based on locally estimating the entire depth map of a query image directly from a repository of 3D images (image depth pairs or stereo pairs) using a nearest-neighbour regression type idea.
Authors and Affiliations
Anusha M Sidhanti| Electronics and communications Dept VDRIT College of engineering and Technology Haliyal, India, Prof. Jyothsna C| Electronics and communications Dept VDRIT College of engineering and Technology Haliyal, India, Mounesh V M| Electronics and communications Dept VDRIT College of engineering and Technology Haliyal, India
Keywords
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