通过航拍图像自动构建光伏电站高精度三维模型。
Detailed Aerial Mapping of Photovoltaic Power Plants Through Semantically Significant Keypoints
- 利用航拍图中的视觉关键点识别模块布局，实现精细化建模。
- 在两个电站上验证，成功融合多图数据生成带语义结构的3D模型。
- 无需第三方数据，适合电站运维人员快速获取精确地图。
准确且最新的光伏（PV）电站模型对优化运行与维护至关重要，但通常难以获取。本文提出一种基于航拍全景图像的新型光伏电站测绘方法，实现自动化建模，无需依赖第三方数据。该方法利用电站的结构布局特征，将建模细化至单个光伏组件级别。通过在全景图像中进行组件语义分割，并推断每张图像中的结构信息，将组件分配到具体的支架、排和列。我们识别与布局相关的视觉关键点，用于在保持结构完整性的前提下融合多张图像的检测结果。该方法在两个不同电站上进行了实验验证与评估。最终融合的3D位置与语义结构生成了一个紧凑的地理参考模型，适用于电站维护。
原文摘要 · Abstract (English)
An accurate and up-to-date model of a photovoltaic (PV) power plant is essential for its optimal operation and maintenance. However, such a model may not be easily available. This work introduces a novel approach for PV power plant mapping based on aerial overview images. It enables the automation of the mapping process while removing the reliance on third-party data. The presented mapping method takes advantage of the structural layout of the power plants to achieve detailed modeling down to the level of individual PV modules. The approach relies on visual segmentation of PV modules in overview images and the inference of structural information in each image, assigning modules to individual benches, rows, and columns. We identify visual keypoints related to the layout and use these to merge detections from multiple images while maintaining their structural integrity. The presented method was experimentally verified and evaluated on two different power plants. The final fusion of 3D positions and semantic structures results in a compact georeferenced model suitable for power plant maintenance.
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