Reconstruction method and system for processing three-dimensional point cloud containing main plane scene

Abstract

The invention proposes a reconstruction method and system for processing three-dimensional point cloud containing a main plane scene. The method comprises the following steps of obtaining a multi-angle image of a static scene by using a camera with known internal parameters; detecting characteristic points of the image, and matching characteristic points of any two images to obtain a matched point pairs and obtaining a matched point sequence by projecting the same scene point; for image pairs containing the preset number of matched point pairs, obtaining a basic array between the image pairs according to the matched points, and storing corresponding space plane point sets; determining the corresponding position relationship between the image pairs according to the basic array; realizing camera fusion and three-dimensional point reconstruction in a standard coordinate frame according to the corresponding position relationship between the image pairs; and optimizing the reconstruction result of the three-dimensional point cloud. The reconstruction method for processing three-dimensional point cloud containing main plane scene of the invention can overcome defects of the existing reconstruction method for processing three-dimensional point cloud and can realize the three-dimensional reconstruction not depending on the scene.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to a method for reconstructing a three-dimensional point cloud model of a scene from a multi-view two-dimensional image. Background technique [0002] Establishing a real and reliable 3D point cloud model for real objects and scenes is an important part of many 3D systems. The quality of the built model plays a very important role in the actual effect of 3D technology in heritage protection, virtual reality, video games and many other applications. Among them, people have done a lot of research on 3D reconstruction based on ordinary light 2D images, and there are still many areas to be improved. [0003] DEGENSAC (DEGENerate SAmple Consensus) is an improved algorithm of RANSAC (RANdom SAmplecomsensus), which can deal with the problem of epipolar geometry calculation of general scenes and image pairs containing principal plane scenes. The basic idea of ​​the algorithm is ...

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Problems solved by technology

[0007] For this reason, an object of the present invention is to propose a method for processing 3D point cloud reconstruction of scenes containing principal planes, through which some deficiencies of existing 3D point cloud reconstruction methods can be solved, thereby realizing 3D reconstruction without scene dependence

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