Classification of Outdoor 3D Lidar Data Based on Unsupervised Gaussian Mixture Models

Three-dimensional point clouds acquired with lidars are an important source of data for the classification of outdoor environments by autonomous terrestrial robots. We propose a two-layer classification model. The first layer consists of a Gaussian mixture model. This model is determined in a traini...

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