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Reconstructing 3D Buildings from LIDAR using Level Set Methods

机译:使用LIDAR使用级别设置方法重建3D建筑物

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We present a novel approach to reconstructing cities and buildings from LIDAR data using level set methods. Traditional approaches to building extraction from LIDAR data use image segmentation algorithms to determine the outlines of rooftops, estimation of height/depth maps, polygonal mesh generation and extrusion to generate 3D models resulting in buildings with high quality rooftops but flat sides with little or no detail shown on vertical surfaces (e.g. overhangs and windows on walls). Texturing these flat side polygons with aerial and geo-registered ground imagery create acceptable photo-realistic models although the resulting buildings are generally not geometrically accurate causing stretching and waviness in texture-mapping. Our approach uses the LIDAR data directly as constraints in a variational framework and can estimate the geometry more accurately and demonstrate its effectiveness with simulated data.
机译:我们使用水平集方法提出了一种从LIDAR数据重建城市和建筑物的新方法。传统方法从LIDAR数据建立提取,使用图像分割算法来确定屋顶的轮廓,高度/深度映射估计,多边形网格产生和挤出,以产生具有高质量屋顶的建筑物,而是具有很少或没有细节的平坦侧面显示在垂直表面(例如墙壁上的悬垂和窗户)。纹理这些平面多边形具有空中和地理注册地理图像,营造可接受的照片 - 现实模型,尽管所得到的建筑通常不是几何准确,导致纹理映射中的伸展和波纹。我们的方法直接使用LIDAR数据作为变分框架中的约束,并且可以更准确地估计几何体,并展示其与模拟数据的有效性。

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