Data frame aware optimized Octomap-based dynamic object detection and removal in Mobile Laser Scanning data

The Mobile Laser Scanning (MLS) data inevitably includes dynamic objects because there are always other vehicles (e.g., other cars, motorbikes, bikes, etc.) moving in the area near the MLS data collection vehicle on the road. These dynamic objects need to be removed in advance for many point cloud applications. This paper designs an efficient...

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...

Detection and reconstruction of static vehicle-related ground occlusions in point clouds from mobile laser scanning

Vehicle-related ground occlusion is a common problem in MLS data. This study aims to design a detection and reconstruction method of static vehicle-related ground occlusion for MLS data. Ground extraction and vehicle segmentation are performed on the input point cloud data in advance. Then an α-shape boundary based on the prior vehicle...

Fundamentals, implementations and experimental benchmarks of nD-polytype queries on point cloud data sets

As an extension to 2D polygonal queries, the nD-polytope queries on point clouds also play a crucial rolein nD GIS applications such as the perspective view selection. This report rst denes the nD-polytopemathematically, and then develops an ecient nD-polytope querying solution by extending an index-organized table (IOT) approach. The solution...

Executing convex polytope queries on nD point clouds

Efficient spatial queries are frequently needed to extract useful information from massive nD point clouds. Most previous studies focus on developing solutions for orthogonal window queries, while rarely considering the polytope query. The latter query, which includes the widely adopted polygonal query in 2D, also plays a critical role in...

An efficient nd-point data structure for querying flood risk

Governments use flood maps for city planning and disaster management to protect people and assets. Flood risk mapping projects carried out for these purposes generate a huge amount of modelling results. Previously, data submitted are highly condensed products such as typical flood inundation maps and tables for loss analysis. Original...

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...

Visualization of point cloud models in mobile augmented reality using continuous level of detail method

Point clouds have become one of the most popular sources of data in geospatial fields due to their availability and flexibility. However, because of the large amount of data and the limited resources of mobile devices, the use of point clouds in mobile Augmented Reality applications is still quite limited. Many current mobile AR applications...

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...

Indoor routing on logical network using space semantics

An indoor logical network qualitatively represents abstract relationships between indoor spaces, and it can be used for path computation. In this paper, we concentrate on the logical network that does not have notions for metrics. Instead, it relies on the semantics and properties of indoor spaces. A navigation path can be computed by...

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...

Managing Large Multidimensional Array Hydrologic Datasets: A Case Study Comparing NetCDF and SciDB

Management of large hydrologic datasets including storage, structuring, indexing and query is one of the crucial challenges in the era of big data. This research originates from a specific data query problem: time series extraction at specific locations takes a long time when a large multidimensional dataset is stored in non-chunked NetCDF...