基于多幅图像的被动三维重建方法综述

Machine Graphics and Vision Pub Date : 2012-01-14 DOI:10.22630/mgv.2014.23.3.5

M. Siudak, P. Rokita

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引用次数: 13

摘要

基于其图像和录像的三维场景重建的研究已经进行了多年。因此，关于如何处理重建问题有许多方法。本文的目标是介绍最重要的重建方法，包括立体视觉，运动形状，散焦形状，形状形状轮廓。从照片一致性的形状。本文中解释的所有算法都可以用于普通照明场景中使用休闲相机拍摄的图像(被动方法)。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Survey of Passive 3D Reconstruction Methods on the Basis of More than One Image

The research on the 3D scene reconstruction on the basis of its images and video recordings has been in progress for many years. As a~result there is a~number of methods concerning how to manage the reconstruction problem. This article's goal is to present the most important methods of reconstruction including stereo vision, shape from motion, shape from defocus, shape form silhouettes. shape from photo-consistency. All the algorithms explained in this article can be used on images taken with casual cameras in an ordinary illuminated scene (passive methods).

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来源期刊

Machine Graphics and Vision Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

0.40

自引率

0.00%

发文量

期刊介绍： Machine GRAPHICS & VISION (MGV) is a refereed international journal, published quarterly, providing a scientific exchange forum and an authoritative source of information in the field of, in general, pictorial information exchange between computers and their environment, including applications of visual and graphical computer systems. The journal concentrates on theoretical and computational models underlying computer generated, analysed, or otherwise processed imagery, in particular: - image processing - scene analysis, modeling, and understanding - machine vision - pattern matching and pattern recognition - image synthesis, including three-dimensional imaging and solid modeling