| 标题 |
 An automatic workflow for orientation of historical images with large radiometric and geometric differences 具有较大辐射和几何差异的历史图像定向的自动工作流程
相关领域
工作流程
方向（向量空间）
计算机科学
人工智能
计算机视觉
特征提取
匹配（统计）
特征（语言学）
软件
摄影测量学
模式识别（心理学）
数据库
数学
几何学
哲学
统计
语言学
程序设计语言
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| 网址 | |
| DOI | |
| 其它 | This contribution proposes a workflow for a completely automatic orientation of historical terrestrial urban images. Automatic structure from motion (SfM) software packages often fail when applied to historical image pairs due to large radiometric and geometric differences causing challenges with feature extraction and reliable matching. As an innovative initialising step, the proposed method uses the neural network D2-Net for feature extraction and Lowe’s mutual nearest neighbour matcher. The principal distance for every camera is estimated using vanishing point detection. The results were compared to three state-of-the-art SfM workflows (Agisoft Metashape, Meshroom and COLMAP) with the proposed workflow outperforming the other SfM tools. The resulting camera orientation data are planned to be imported into a web and virtual/augmented reality (VR/AR) application for the purpose of knowledge transfer in cultural heritage. |
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