Abstract: A method for real-time acquisition of point-cloud data of an ongoing scanning process, comprising a recording phase iteratively performed using an external-memory algorithm comprising an acquisition pipeline performed with parallel threads and an eviction pipeline, wherein a master thread comprises processing a master tree and a node cache, wherein the acquisition pipeline comprises continuously receiving the point-cloud data in input buffers, computing a local tree for each of a plurality of local threads, redistributing the point-cloud data onto local nodes, determining, for each local node whether the master tree comprises a corresponding node or not, either adding the point cloud data or creating the corresponding node in the master tree, wherein the eviction pipeline comprises evicting, during the ongoing scanning process, point cloud data from the node cache and writing it to one or more hard drives.

Abstract: A method for pre-processing point clouds comprising large amounts of point data. The method comprises converting the points' coordinates to Morton indices, sorting the Morton indices and sequentially determining intervals based on predefined criteria, which intervals define the leaf nodes and form the basis and starting point for the generation of a tree index structure comprising the leaf nodes, nodes, branches and nodes connecting the branches. Point data contained within a node or sub-trees of a node are quantizable.

Abstract: A method for pre-processing point clouds comprising large amounts of point data. The method comprises converting the points' coordinates to Morton indices, sorting the Morton indices and sequentially determining intervals based on predefined criteria, which intervals define the leaf nodes and form the basis and starting point for the generation of a tree index structure comprising the leaf nodes, nodes, branches and nodes connecting the branches. Point data contained within a node or sub-trees of a node are quantizable.