针对美国新奥尔良地区稀疏的LiDAR （Light Detecting and Ranging）点云数据，提出了一种基于LiDAR数据和卫星图像进行融合的居民区建筑物重建方法.该方法利用LiDAR数据点集的边界来定位卫星图像上的感兴趣区域，利用从感兴趣区域中提取的关键提示线来实现屋顶的分割，从而得到属于每个建筑物的屋顶点.然后，基于三角面片的法向量方向信息对其进行聚类，根据法向量之间的关系进行屋顶类型识别，从而实现居民区建筑物的重建.实验表明，该方法在进行居民区建筑物重建时，能达到较高的重建率，且重建所需时间合理，能够满足虚拟现实系统的需要.
Abstract
Facing the sparse LiDAR (Light Detecting and Ranging) data of New Orleans area in America
a new residential building reconstruction method based on the fusion of LiDAR and satellite imagery is proposed.The main contribution of this work is the automatic isolation of roof points and roof type recognition.Using LiDAR data boundary to identify the ROI area in satellite imagery
and using cue lines extracted from ROI areas
the building roofs are isolated.Then
based on the relationship of normal vectors
building types are recognized
and then buildings are reconstructed.Experiments show that our method can successfully reconstruct residential buildings given relatively sparse LiDAR samples
achieve a high reconstruction rate in a reasonably short time
which meet the requirement of virtual reality systems.
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