PCL 点云最小生成树算法可视化：茎干识别

The code you provided is performing Principal Component Analysis (PCA) on a point cloud and fitting a line to the data. Here is a breakdown of the code:
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1. The code starts by including the necessary libraries and defining some typedefs for point cloud types.
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2. A Graph class is defined to represent a connected, undirected, and weighted graph. It has methods for adding edges and finding the minimum spanning tree using Kruskal's algorithm.
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3. The main function loads a point cloud from a PLY file and computes the centroid and normals of the points.
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4. The code creates a graph with the number of vertices equal to the number of points in the cloud and calculates the edge weights based on the Euclidean distance between points.
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5. The KruskalMST function is called to find the minimum spanning tree of the graph. The resulting edges are stored in the "result" vector.
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6. The code then iterates over the edges in the result vector and checks if the endpoints of the edge are connected to a set of "singlejiedian" points. If the weight of the