Abstract: Filtering on rock mass point clouds is an important step in 3D rock mass reconstruction. This work focuses on rock mass point clouds and we propose a vegetation filtering method based on multi-dimensionality features and MLP(multi-layer perceptron). This method firstly calculates multi-dimensionality features for each point. Then, MLP is used for training the classifier, which can be applied in vegetation filtering. We analyze the availability of multi-dimensionality features and select the best MLP model through different experimental processes. The experimental results show that the proposed method has a higher precision than other classifiers and it can be better applied in the field of rock mass point cloud vegetation filtering.

Key words: rock mass point clouds, vegetation filtering, dimensionality features, multi-layer perceptron