Research on Point Cloud Alignment Image Processing Algorithm based on Wind Farm Plot Monitoring

In this paper, image processing and artificial intelligence technology are used to monitor the plot movement of wind farms. The primary objective of point cloud alignment is to determine the optimal spatial correspondence among two or more point cloud datasets. This study aims to exploit information from different resolution levels in point cloud data, enhancing alignment accuracy. Thus, we propose a multi-scale feature fusion point cloud alignment algorithm (Multi-Scale Matcher) incorporating the cross-attention mechanism. Experiments conducted on the ModelNet40 dataset demonstrate that the proposed method significantly enhances the accuracy of point cloud alignment. This algorithm can be applied to the monitoring of block movement well.