Multi-view stereo matching three-dimensional reconstruction method of disordered image

Abstract

The invention belongs to the field of three-dimensional reconstruction technology, and relates to a multi-view stereo matching three-dimensional reconstruction method of a disordered image. According to the method of the invention, at a view selection algorithm part, 1), for aiming at a global view selection process, firstly a decision condition is introduced; and furthermore the number of views in a candidate view set is fixed adaptively instead of the view set with fixed number of views. No scoring is performed on the views which do not satisfy a condition in an algorithm. Along with continuous expansion of an application range, the number of views in an experiment data set gradually increases, and reduction of view selection time is very important. 2), For a local view algorithm, the method improves a weight influence factor of a polar plane included angle between a neighbor view and a reference view, so that the selected neighbor view is more accurate and more representative. 3), In a view matching area increasing process, the invention provides an adaptive shape space plane sheet algorithm, an adaptive shape can adaptively adapt boundary information, thereby better matching a result.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional reconstruction, and relates to a three-dimensional reconstruction method for multi-view stereo matching of disordered images. Background technique [0002] The 3D reconstruction process of multi-view stereo matching of unordered graphics is that the camera collects the view set of the scene from multiple perspectives, and then obtains the depth information of the scene through multi-view stereo matching to reconstruct the 3D model of the scene. At present, according to the depth acquisition methods, there are mainly active and passive methods. The active method refers to the use of relatively mature equipment at this stage to directly obtain depth information, such as structured light scanners, which obtain the same name points of image pixels by encoding and decoding projection stripes, and then estimate depth information through techniques such as triangulation; Microsoft's Kinect-V2 ...

AI Technical Summary

Problems solved by technology

These devices can obtain relatively accurate depth information in some specific scenarios, but the devices are complex and not easy to carry, have high requirements for natural lighting, limited scope of application of the scene, and high cost

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