Dense three-dimensional reconstruction method and system based on multi-scale geometric consistency guidance

Abstract

The invention discloses a dense three-dimensional reconstruction method and system based on multi-scale geometric consistency guidance, and belongs to the field of computer vision, and the method comprises the steps: building an image pyramid based on an image set; carrying out depth estimation on the most rough scale of the image pyramid by utilizing photographing consistency, and acquiring a depth map on the most rough scale; taking the most rough depth image on the scale as a depth image on the current scale, sequentially carrying out upsampling and error depth estimation correction on thedepth image on the current scale, and carrying out optimization by utilizing geometric consistency to obtain an optimized depth image on the next scale; taking the optimized depth map of the next scale as a depth map of the current scale, and then carrying out upsampling, correction and optimization until optimized depth maps of all original images in the image set are obtained; and fusing the optimized depth maps of all the original images to obtain dense three-dimensional point cloud. The depth information of the weak texture area can be estimated, and the depth information of the detail area can be kept.

Description

technical field [0001] The invention belongs to the field of computer vision, and more specifically relates to a dense three-dimensional reconstruction method and system guided by multi-scale geometric consistency. Background technique [0002] The patch matching stereo vision method basically follows a 4-step process: random initialization, propagation, view selection and refinement. Among them, the view selection determines the set of aggregated views for each pixel of the current reference image. For a certain pixel in the reference image, the mining of its aggregated view set depends heavily on the similarity between the patch delineated when the pixel is matched and the patch formed by the corresponding pixels in the neighboring views. However, in order to comprehensively consider the depth change and relatively smooth area, the pixel area delineated for measuring the similarity of the patch is usually not too large. Thus, for weakly textured regions, such usual regio...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a dense 3D reconstruction method and system based on multi-scale geometric consistency guidance, thereby solving the problem of not considering the depth of the weak texture area in the multi-scale solution in the prior art The technical problem of estimating reliability constraints and the resulting loss of detail region depth estimation

Images