Three-dimensional reconstruction method based on GPU parallel acceleration

Abstract

The invention belongs to the field of machine vision research, and particularly relates to a three-dimensional reconstruction method based on GPU parallel acceleration. The method mainly comprises thefollowing steps: initializing an algorithm; loading the image sequence modulated by the structured light, and copying the image sequence in the computer memory to a common memory of the GPU equipmentside in parallel; the GPU is used for carrying out background segmentation on images shot by the left camera and the right camera in parallel, three-dimensional reconstruction is only carried out onsegmented foreground targets, redundant calculation is reduced, and the calculation efficiency is improved; solving an image sequence phase principal value by using GPU parallel acceleration and carrying out phase unwrapping to obtain an absolute phase value; distortion correction is carried out on the phase unwrapped image; stereoscopic matching is carried out in a serial and parallel combined mode, that is, serial processing is carried out on local areas of an image, parallel processing is carried out between the areas, and stereoscopic matching is carried out; disparity map preprocessing; and calculating a three-dimensional point cloud according to the disparity map. According to the method, the parallel computing capability of the GPU is fully utilized, the overall computing speed of the algorithm is increased, and the application scene of three-dimensional reconstruction is expanded.

Description

technical field [0001] The invention belongs to the field of machine vision research, in particular to a three-dimensional reconstruction method based on GPU parallel acceleration. Background technique [0002] Three-dimensional reconstruction technology is one of the important topics in machine vision research, which refers to the restoration of the three-dimensional geometric shape of three-dimensional objects through the images of three-dimensional objects. The general methods of 3D reconstruction include triangulation through binocular parallax principle of dual cameras, or spatial encoding through structured light, and depth information through triangulation. [0003] Due to the inherent complexity of the 3D reconstruction algorithm, the computational complexity of the 3D reconstruction algorithm is large, and the reconstruction speed has always been the bottleneck restricting the application of 3D reconstruction technology. Although the number of CPU cores has increas...

AI Technical Summary

Problems solved by technology

[0003] Due to the inherent complexity of the 3D reconstruction algorithm, the computational complexity of the 3D reconstruction algorithm is large, and the reconstruction speed has always been the bottleneck restricting the application of 3D reconstruction technology.

Although the number of CPU cores has increased, its instruction system is more inclined to process tasks and is not suitable for parallel processing of data, so the improvement in computing performance is not obvious

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