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ANALYSIS OF TWO TRIANGLE-BASED MULTI-SURFACE REGISTRATION ALGORITHMS OF IRREGULAR POINT CLOUDS

机译:不规则点云两三角形多表面配准算法分析

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The registration of multiple surface point clouds into a common reference frame is a well addressed topic, and the Iterative Closest Point (ICP) is - perhaps - the most used method when registering laser scans due to their irregular nature. In this paper, we examine the proposed Iterative Closest Projected Point (ICPP) algorithm for the simultaneous registration of multiple point clouds. First, a point to triangular patch (i.e. closest three points) match is established by checking if the point falls within the triangular dipyramid, which has the three triangular patch points as a base and a user-chosen normal distance as the height to establish the two peaks. Then, the point is projected onto the patch surface, and its projection is then used as a match for the original point. It is also shown through empirical experimentation that the Delaunay triangles are not a requirement for establishing matches. In fact, Delaunay triangles in some scenarios may force blunders into the final solution, while using the closest three points leads to avoiding some undesired erroneous points. In addition, we review the algorithm by which the ICPP is inspired, namely, the Iterative Closest Patch (ICPatch); where conjugate point-patch pairs are extracted in the overlapping surface areas, and the transformation parameters between all neighbouring surfaces are estimated in a pairwise manner. Then, using the conjugate point-patch pairs, and applying the transformation parameters from the pairwise registration as initial approximations, the final surface transformation parameters are solved for simultaneously. Finally, we evaluate the assumptions made and examine the performance of the new algorithm against the ICPatch.
机译:将多个表面点云的登记到公共参考帧中是一个良好的解决主题,并且迭代最接近的点(ICP)是 - 可能是当由于其不规则性而注册激光扫描时最常用的方法。在本文中,我们检查了用于同时登记多点云的建议迭代最接近的投影点(ICPP)算法。首先,通过检查点落在三角形二维拉米内,建立到三角形贴片(即最接近的三个点)匹配的点,该点在三角形二维拉米德内具有三个三角形补丁点作为基础,并且用户选择的正常距离作为建立的高度两个峰。然后,将点投影到贴片表面上,然后将其投影用作原始点的匹配。通过实证实验还通过实证实验表明,Delaunay三角形不是建立匹配的要求。事实上,在某些情况下,Delaunay三角形可能会强迫漏洞进入最终解决方案,同时使用最接近的三个点导致避免一些不期望的错误点。此外,我们审查了ICPP激发的算法,即迭代最近的补丁(ICPatch);其中共轭点贴片对在重叠表面区域中提取,并且所有相邻表面之间的变换参数以成对方式估计。然后,使用共轭点贴片对,并将变换参数从成对登记应用作为初始近似,同时解决最终表面变换参数。最后,我们评估了对ICPatch的新算法的假设和检查了新算法的性能。

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