Towards 10^15-level point clouds management - a nD PointCloud structure

Drastically increasing production of point clouds as well as modern application fields like robotics and virtual reality raises essential demand for smart and highly efficient data management. Effective tools for the managing and direct use of large point clouds are missing. Current state-of-the-art database management systems (DBMS) present...

Management of large indoor point clouds: An initial exploration

Indoor navigation and visualization become increasingly important nowadays. Meanwhile, the proliferation of new sensors as well as the advancement of data processing provide massive point clouds to model the indoor environment in high accuracy. However, current state-of-the-art solutions fail to manage such large datasets efficiently. File...

HistSFC: Optimization for nD massive spatial points querying

Space Filling Curve (SFC) mapping-based clustering and indexing works effectively for point clouds management and querying. It maps both points and queries into a one-dimensional SFC space so that B+- tree could be utilized. Based on the basic structure, this paper develops a generic HistSFC approach which utilizes a histogram tree recording...

An optimized SFC approach for nD window querying on point clouds

Dramatically increasing collection of point clouds raises an essential demand for highly efficient data management. It can also facilitate modern applications such as robotics and virtual reality. Extensive studies have been performed on point data management and querying, but most of them concentrate on low dimensional spaces. High...

Point clouds and Hydroinformatics

Point cloud is made up of a multitude of three-dimensional (3D) points with one or more attributes attached. Point cloud is the third data paradigm in addition to the well-established object (vector) and gridded (raster) representations, since point cloud data can be directly collected, computed, stored, and analyzed without converting to other...

Organizing and visualizing point clouds with continuous levels of detail

Point clouds contain high detail and high accuracy geometry representation of the scanned Earth surface parts. To manage the huge amount of data, the point clouds are traditionally organized on location and map-scale; e.g. in an octree structure, where top-levels of the tree contain few points suitable for small scale overviews and lower...