基于传感器拓扑的单纯复形重构
Sensor-topology based simplicial complex reconstruction
摘要：
我们提出了一种新的方法，用于从移动激光扫描（MLS）的3D点云重建单纯形复合体（结合点，边和三角形）。我们的主要目标是产生一个场景的重建，是适应当地的几何形状的对象。我们的方法使用MLS传感器的固有拓扑结构来定义点之间的空间邻接关系。然后，我们调查相邻点之间的每个可能的连接，并通过搜索场景中的共线结构或垂直于激光束的结构来过滤它们。接下来，我们为每个三重自连接边创建三角形。最后，我们改进了这种方法的正则化的基础上的三角形共面性和共线的剩余边缘。我们将我们的结果与基于边长度的朴素单纯复形重建进行比较。
英文摘要：
We propose a new method for the reconstruction of simplicial complexes (combining points, edges and triangles) from 3D point clouds from Mobile Laser Scanning (MLS). Our main goal is to produce a reconstruction of a scene that is adapted to the local geometry of objects. Our method uses the inherent topology of the MLS sensor to define a spatial adjacency relationship between points. We then investigate each possible connexion between adjacent points and filter them by searching collinear structures in the scene, or structures perpendicular to the laser beams. Next, we create triangles for each triplet of self-connected edges. Last, we improve this method with a regularization based on the co-planarity of triangles and collinearity of remaining edges. We compare our results to a naive simplicial complexes reconstruction based on edge length.
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