Computer-implemented method for real-time acquisition and visualization of point-cloud data of an ongoing scanning process, the point-cloud data comprising coordinates for a multitude of points, the method comprising - providing a node cache, - providing a level-of-detail structure having a master tree and a local structure comprising a plurality of local trees (23a-c), particularly wherein the level-of-detail structure is an octree structure, and - visualizing at least a subset of the point-cloud data to a user before the ongoing scanning process ends, characterized in that the method comprises a recording phase that is iteratively performed using an external-memory algorithm, the recording phase comprising an acquisition pipeline and an eviction pipeline, wherein the acquisition pipeline is performed with a plurality of parallel threads comprising at least one master thread and a plurality of local threads, wherein the master thread comprises processing the master tree and the node cache, wherein the acquisition pipeline comprises - continuously receiving the point-cloud data in one or more input buffers, - computing a local tree (23a-c) for each of the local threads, - redistributing point-cloud data of the input buffers onto local nodes of the local tree structure, - determining, for each local node whether the master tree comprises a corresponding node or not, and - if the master tree comprises the corresponding node, determining if point cloud data for this node is present in the node cache, wherein if the point cloud data is present, the point cloud data is added to the node, and - if the master tree does not comprise the corresponding node, creating the corresponding node in the master tree and writing the point-cloud data comprised in the respective local node to the node cache, 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 (34, 35). - providing a node cache, - providing a level-of-detail structure having a master tree and a local structure comprising a plurality of local trees (23a-c), particularly wherein the level-of-detail structure is an octree structure, and - visualizing at least a subset of the point-cloud data to a user before the ongoing scanning process ends, characterized in that the method comprises a recording phase that is iteratively performed using an external-memory algorithm, the recording phase comprising an acquisition pipeline and an eviction pipeline, wherein the acquisition pipeline is performed with a plurality of parallel threads comprising at least one master thread and a plurality of local threads, wherein the master thread comprises processing the master tree and the node cache, wherein the acquisition pipeline comprises the method comprises a recording phase that is iteratively performed using an external-memory algorithm, the recording phase comprising an acquisition pipeline and an eviction pipeline, wherein the acquisition pipeline is performed with a plurality of parallel threads comprising at least one master thread and a plurality of local threads, wherein the master thread comprises processing the master tree and the node cache, wherein the acquisition pipeline comprises - continuously receiving the point-cloud data in one or more input buffers, - computing a local tree (23a-c) for each of the local threads, - redistributing point-cloud data of the input buffers onto local nodes of the local tree structure, - determining, for each local node whether the master tree comprises a corresponding node or not, and - if the master tree comprises the corresponding node, determining if point cloud data for this node is present in the node cache, wherein if the point cloud data is present, the point cloud data is added to the node, and - if the master tree does not comprise the corresponding node, creating the corresponding node in the master tree and writing the point-cloud data comprised in the respective local node to the node cache,