CUDA architecture parallel optimization three-dimensional deformation measurement method based on novel correlation function constraint

Abstract

The invention discloses a CUDA Architecture parallel optimization three-dimensional deformation measurement method based on novel correlation function constraints. The method comprises the following steps: acquiring a relative pose parameter relationship among multiple cameras; building a novel correlation function of speckle stereo registration based on a joint constraint relation between cameras, wherein the novel correlation function limits search of stereo registration points between image pairs in an epipolar nearby area, and sampling speckles in different sequence images are subjected to time sequence registration and stereo registration; and performing three-dimensional reconstruction on the space coordinates of the speckle spots. A novel correlation function is built through a joint constraint relationship among multiple cameras; the search of the three-dimensional registration points between the image pairs is limited in an area near the epipolar line instead of the whole image, so that the search space is reduced; influence factors of three-dimensional parallax on speckle three-dimensional registration are comprehensively considered, a parallel mechanism optimization scheme based on an established novel correlation function is designed, and the precision and the speed of three-dimensional deformation measurement are respectively improved from two aspects of algorithm characteristics and a hardware coupling mechanism.

Description

technical field [0001] The invention belongs to the technical field of non-contact measurement of three-dimensional deformation based on vision technology, and in particular relates to a CUDA framework parallel optimization three-dimensional deformation measurement method and system based on novel correlation function constraints. Background technique [0002] The three-dimensional deformation information measurement based on the visual measurement mode provides data reference and support for the performance analysis, geometric deformation monitoring, and bearing capacity evaluation of the measured target. However, in the process of three-dimensional deformation measurement, the calculation data scale is large. For example, in order to improve the accuracy of deformation measurement, a large number of speckle points are usually required to participate in the registration operation, so the registration data volume is relatively large. As the size of the image increases, the a...

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Problems solved by technology

[0005] For the measurement of stereoscopic deformation information based on the above-mentioned visual measurement mode, the data volume of speckle point registration is relatively large. At the same time, as the number of image frames and image size increase, the amount of calculation related to speckle sub-regions and the interpolation calculation of sub-pixels The amount will be greatly increased, and the huge time-consuming reduces the technical problem of three-dimensional deformation measurement efficiency. A CUDA architecture based on a new correlation function constraint is proposed to optimize the three-dimensional deformation measurement method and system in parallel. Through the joint constraint relationship between multiple cameras Establish a new type of correlation function, which can limit the search of stereo registration points between image pairs to the area near the epipolar line instead of the entire image, thereby reducing the search space and greatly improving the efficiency and accuracy of 3D deformation measurement

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