Clustering and Segmentation

Abstract

Storing and processing large point cloud datasets represents one of the main bottlenecks of a 3D perception system. Though algorithms that can process individual data frames with low computational resources can be written, their capabilities are hindered as larger quantities of data accumulate. A simple example in this direction can be given by the problem of estimating the best planar model that represents a set of points $\mathcal{P}$.