实时生成高精度正射影像图，解决传统方法延迟高的问题
A-TDOM: Active TDOM via On-the-Fly 3DGS
- 基于动态3D高斯溅射，逐帧优化相机位姿与点云
- 新增区域通过德劳内三角采样增量重建，提升未见区域质量
- 支持近实时输出，适合城市规划等时效性场景
真实数字正射影像图（TDOM）是地球表面的二维客观表示，广泛应用于城市管理、城市规划和土地测绘等领域。然而，传统TDOM生成依赖复杂的离线摄影测量流程，导致显著延迟，难以满足时效性或实时场景需求。此外，相机姿态不准确、数字地表模型（DSM）不完善及遮挡检测错误也会降低TDOM质量。为此，本文提出A-TDOM，一种基于实时3D高斯溅射（On-the-Fly 3DGS）优化的近实时TDOM生成方法。每帧图像到达时，通过实时稀疏运动恢复（SfM）计算其位姿与稀疏点云；新观测区域通过德劳内三角化高斯采样与集成，逐步添加至3D高斯模型，并在未见或粗略建模区域采用自适应训练迭代与学习率进行优化。渲染管线中集成正交溅射，使A-TDOM可在每次3DGS更新后立即生成更新后的TDOM输出。代码已开源：https://github.com/xywjohn/A-TDOM。
原文摘要 · Abstract (English)
True Digital Orthophoto Map (TDOM), a 2D objective representation of the Earth's surface, is an essential geospatial product widely used in urban management, city planning, land surveying, and related applications. However, traditional TDOM generation typically relies on a complex offline photogrammetric pipeline, leading to substantial latency and making it unsuitable for time-critical or real-time scenarios. Moreover, the quality of TDOM may deteriorate due to inaccurate camera poses, imperfect Digital Surface Model (DSM), and incorrect occlusions detection. To address these challenges, this work introduces A-TDOM, a near real-time TDOM generation method built upon On-the-Fly 3DGS (3D Gaussian Splatting) optimization. As each incoming image arrives, its pose and sparse point cloud are computed via On-the-Fly SfM. Newly observed regions are then incrementally reconstructed as additional 3D Gaussians are inserted using a Delaunay triangulated Gaussian sampling and integration and are further optimized via adaptive training iterations and learning rate, especially in previously unseen or coarsely modeled areas. With orthogonal splatting integrated into the rendering pipeline, A-TDOM can actively produce updated TDOM outputs immediately after each 3DGS update. Code is now available at https://github.com/xywjohn/A-TDOM.
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