Using RPM – GMM for TPS interpolation in MCC algorithm

Nguyen Thi Huu Phuong


The author mentions the TPS interpolation improvement using RPM - GMM, where EM is used to initialize the parameters for the Gaussian model. Using EM algorithm in model calculation in TPS-RPM will help solve the symmetry point in this point matching process. With the idea of using Robust point matching (RPM), this is the optimal search technique in the spatial transformation of the point cloud.. RPM is very powerful in removing noise and exceptions. This is an algorithm that uses iteration with 2 steps of calculating probability and updating is quite similar to EM algorithm. Therefore, the authors have researched and tested the TPS interpolation based on RPM-GMM. With the test data set in Bac Ninh city of Quang Ninh province, the classification results with MCC when using TPS-RPMGMM compared to MCC version 2.1 announced in 2018 achieved higher results and non-ground class are classified into more detail: buildings and vegetation.


MCC, RPM, EM, LiDAR point cloud, TPS interpolation

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