Depth camera-oriented high-precision three-dimensional reconstruction method and system

Abstract

The invention discloses a depth camera-oriented multi-view three-dimensional reconstruction method and system. The method comprises the steps of obtaining multiple pairs of images of a real scene fromdifferent angles according to a depth camera, wherein each pair of images comprises a color image and a depth image; according to a feature point detection algorithm, obtaining two-dimensional feature points and feature descriptors on the color images, calculating a confidence degree between the feature descriptors corresponding to any two color images respectively, and obtaining a feature matching relationship; according to the feature matching relationships and the corresponding depth images, obtaining corresponding three-dimensional images, reversely projecting two-dimensional feature points to a camera coordinate system, and obtaining three-dimensional points on the three-dimensional images; according to the two-dimensional feature points and the three-dimensional points, calculatingabsolute attitude of the camera; and according to the absolute attitude of the camera, mapping the three-dimensional points to the camera coordinate system, and obtaining an initial three-dimensionalmodel of the scene. By adopting the method or the system, the high-precision three-dimensional scene model can be recovered from the image sequence collected by the depth camera.

Description

technical field [0001] The invention relates to the fields of computer vision and computer graphics, in particular to a high-precision three-dimensional reconstruction method and system for depth cameras. Background technique [0002] High-precision 3D reconstruction has always been one of the hot research issues in the field of computer vision and graphics, and its purpose is how to efficiently restore the 3D model of the scene from the input image sequence. At the same time, 3D reconstruction technology plays an irreplaceable role in the game industry, military simulation, agriculture and industry, augmented reality, virtual reality, scene monitoring, map navigation and automatic driving. Due to the influence of factors such as illumination changes in the scene, occlusion between objects, scene aggregation, repetitive structure, and noise in the collected data, it is difficult for the traditional manual-based active 3D modeling method to reconstruct the real 3D scene mode...

AI Technical Summary

Problems solved by technology

Due to the influence of factors such as illumination changes in the scene, occlusion between objects, scene aggregation, repetitive structure, and noise in the collected data, it is difficult for the traditional manual-based active 3D modeling method to reconstruct the real 3D scene model, cannot recover high-precision 3D scene model contained in a large number of image sequences

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