Hasso-Plattner-Institut
  
Hasso-Plattner-Institut
Prof. Dr. Jürgen Döllner
  
 

Publications

Out-of-Core GPU-based Change Detection in Massive 3D Point Clouds

Richter, Rico and Kyprianidis, Jan Eric and Döllner, Jürgen
Transactions in GIS, vol. 17(5):724-741 2013

DOI: DOI: 10.1111/j.1467-9671.2012.01362.x

Abstract:

If sites, cities, and landscapes are captured at different points in time using technology such as LiDAR, large collections of 3D point clouds result. Their efficient storage, processing, analysis, and presentation constitute a challenging task because of limited computation, memory, and time resources. In this work, we present an approach to detect changes in massive 3D point clouds based on an out-of-core spatial data structure that is designed to store data acquired at different points in time and to efficiently attribute 3D points with distance information. Based on this data structure, we present and evaluate different processing schemes optimized for performing the calculation on the CPU and GPU. In addition, we present a point-based rendering technique adapted for attributed 3D point clouds, to enable effective out-of-core real-time visualization of the computation results. Our approach enables conclusions to be drawn about temporal changes in large highly accurate 3D geodata sets of a captured area at reasonable preprocessing and rendering times. We evaluate our approach with two data sets from different points in time for the urban area of a city, describe its characteristics, and report on applications.

BibTeX file

@article{RKD12,
author = { Richter, Rico and Kyprianidis, Jan Eric and Döllner, Jürgen },
title = { Out-of-Core GPU-based Change Detection in Massive 3D Point Clouds },
pages = { 724-741 },
year = { 2013 },
journal = { Transactions in GIS },
volume = { 17 },
number = { 5 }
}

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last change: Mon, 14 Oct 2013 14:31:46 +0200