Three-dimensional view acquisition method

Abstract

The invention discloses a three-dimensional view acquisition method, which comprises the following steps of: setting computation variables in an image interface and an image processor; changing gray scales and layering; computing a cost function matrix; computing an original information storage matrix; computing a confidence matrix and depth map data; initializing a shifting distance, and shifting all pixels in a two-dimensional view into a two-dimensional virtual view; detecting and removing quantizing noises in the two-dimensional virtual view and errors which are not accordant with a sequence restraint, and correcting the errors by using the sequence restraint; detecting void areas in the two-dimensional virtual view and filling the void areas with pixels in a background area; and generating the three-dimensional view. With the characteristics and advantages of developing the parallel processing mode of the image processor, the method realizes the parallel computation of the conventional three-dimensional matching algorithm and the image description algorithm under a graphic processing unit (GPU) frame, so that computation efficiency is improved and real-time binocular visual demonstration is realized.

Description

technical field [0001] The invention relates to the technical fields of computer vision and computer image rendering, in particular to a method for acquiring a three-dimensional view. Background technique [0002] Three-dimensional images and displays are an important form of expression for future information systems. Three-dimensional images and displays are clearly layered and colorful, and have a strong visual impact, allowing viewers to stay longer and leave a deep impression; The images and displays are real and lifelike, the characters are ready to appear, there is an immersive feeling, and there is a high artistic appreciation value. Just because three-dimensional images and videos have the characteristics that these plane images and videos do not have, they have broad application prospects in fields such as computer display, television, video, robotics, measurement, inspection, medical treatment, advertising media, and electronic games. The reason why the human eye ...

AI Technical Summary

Problems solved by technology

The method based on local correlation has many problems such as serious noise, poor effect on the weak texture area of ​​the image and poor robustness, and it is difficult to obtain high-quality stereoscopic reconstruction effect; the method based on dynamic programming is prone to stripe effect at the edge of the object

And for real-time applications, the amount of calculation is still too large

[0005] It can be seen that there are still the following problems: first, the algorithm that can generate a high-quality depth map is very slow; second, the algorithm that can quickly generate a depth map obtains a relatively poor quality depth map

However, such projection and backprojection are computationally expensive and require the parameters of the real camera corresponding to the 2D reference view for the entire rendering process

In practice, a very cumbersome calibration process is required to obtain the parameters of the real camera

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