![]() ![]() It demonstrates the ability and the computational efficiency of the methods on numerous 2D images and discusses their drawbacks and benefits. The second method is based on globally 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. The first is based on learning a point mapping from local image/ attributes, such as color, spatial position. Automatic methods, that 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. Methods involving human operators have been most successful but also time- consuming and costly. Hence many 2D-to-3D image conversion methods have been proposed. Moodbidri, India in the last few years, the availability of 3D content is still less than 2D counterpart. of Computer Science and Engineering Alvas Institute of Engineering and Technology (AIET) ![]() Automatic Learning based 2D-to-3D Image ConversionÄept. ![]()
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