STATE OF THE ART IN HIGH DENSITY IMAGE MATCHING
STATE OF THE ART IN HIGH DENSITY IMAGE MATCHING
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DOI：
10.1111/phor.12063
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发表时间：
2014-06-01
影响因子：
2.4
通讯作者：
Nex, Francesco
中科院分区：
文献类型：
--
作者：
Remondino, Fabio;Spera, Maria Grazia;Nex, Francesco
图像匹配有50多年的历史，最初的实验是为了制图和绘图目的用模拟程序进行的。最近计算机视觉算法和摄影测量方法的集成正在导致有趣的程序，这些程序越来越自动化整个基于图像的3D建模过程。影像匹配是三维建模与制图的关键步骤之一。本文提出了一个严格的审查和分析的四个密集的图像匹配算法，可作为开源和商业软件，生成密集的点云。所采用的八个数据集包括从陆地和空中块记录的场景，用会聚和正常（平行轴）图像采集，并具有不同的尺度。几何分析报告中，每个不同的算法产生的点云相互比较，也地面实况数据。
Image matching has a history of more than 50 years, with the first experiments performed with analogue procedures for cartographic and mapping purposes. The recent integration of computer vision algorithms and photogrammetric methods is leading to interesting procedures which have increasingly automated the entire image-based 3D modelling process. Image matching is one of the key steps in 3D modelling and mapping. This paper presents a critical review and analysis of four dense image-matching algorithms, available as open-source and commercial software, for the generation of dense point clouds. The eight datasets employed include scenes recorded from terrestrial and aerial blocks, acquired with convergent and normal (parallel axes) images, and with different scales. Geometric analyses are reported in which the point clouds produced with each of the different algorithms are compared with one another and also to ground-truth data.