基于立体图像的半自动化三维建筑提取

S. Lee, K. Price, R. Nevatia, T. Heinze, J. Irvine
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引用次数: 2

摘要

从头顶图像中产生地理空间信息通常是一个劳动密集型的过程。分析人员必须从图像中准确地描绘和提取重要特征,如建筑物、道路和土地覆盖。自动特征提取(AFE)工具提供了减少分析人员工作量的前景。本文提出了一种名为iMVS的新工具,用于提取建筑物,并讨论了国家地理空间情报局(NGA)进行的用户测试。iMVS采用半自动化的方法,处理两张或更多的图像,形成一组假设的3-D建筑。当用户点击其中一个建筑顶点时,系统决定哪个假设是最合适的,并提取该建筑。一套强大的编辑工具支持快速清理提取,包括提取复杂的建筑物。iMVS的用户测试提供了对效益的评估,并确定了系统改进的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semi-automated 3-D Building Extraction from Stereo Imagery
The production of geospatial information from overhead imagery is generally a labor-intensive process. Analysts must accurately delineate and extract important features, such as buildings, roads, and landcover from the imagery. Automated feature extraction (AFE) tools offer the prospect of reducing analyst's workload. This paper presents a new tool, called iMVS, for extracting buildings and discusses user testing conducted by the National Geospatial-Intelligence Agency (NGA). Using a semi-automated approach, iMVS processes two or more images to form a set of hypothesized 3-D buildings. When the user clicks on one of the building vertices, the system determines which hypothesis is the best fit and extracts the building. A set of powerful editing tools support rapid clean-up of the extraction, including extraction of complex buildings. User testing of iMVS provides an assessment of the benefits and identifies areas for system improvement.
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