A Simple Semantic-Based Data Storage Layout for Querying Point Clouds
1
Department of Built Environment, Aalto University, P.O. Box 11000, FI-00076 Aalto, Finland
2
Finnish Geospatial Research Institute, Geodeetinrinne 2, FI-02430 Masala, Finland
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(2), 72; https://doi.org/10.3390/ijgi9020072
Received: 10 December 2019
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Revised: 10 January 2020
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Accepted: 19 January 2020
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Published: 22 January 2020
The importance of being able to separate the semantics from the actual (X,Y,Z) coordinates in a point cloud has been actively brought up in recent research. However, there is still no widely used or accepted data layout paradigm on how to efficiently store and manage such semantic point cloud data. In this paper, we present a simple data layout that makes use the semantics and that allows for quick queries. The underlying idea is especially suited for a programming approach (e.g., queries programmed via Python) but we also present an even simpler implementation of the underlying technique on a well known relational database management system (RDBMS), namely, PostgreSQL. The obtained query results suggest that the presented approach can be successfully used to handle point and range queries on large points clouds.
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Keywords:
point cloud; LiDAR; semantic class; RDBMS; point cloud database; NoSQL; python
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Externally hosted supplementary file 1
Doi: 10.5281/zenodo.3540413
Link: https://doi.org/10.5281/zenodo.3540413
MDPI and ACS Style
El-Mahgary, S.; Virtanen, J.-P.; Hyyppä, H. A Simple Semantic-Based Data Storage Layout for Querying Point Clouds. ISPRS Int. J. Geo-Inf. 2020, 9, 72. https://doi.org/10.3390/ijgi9020072
AMA Style
El-Mahgary S, Virtanen J-P, Hyyppä H. A Simple Semantic-Based Data Storage Layout for Querying Point Clouds. ISPRS International Journal of Geo-Information. 2020; 9(2):72. https://doi.org/10.3390/ijgi9020072
Chicago/Turabian StyleEl-Mahgary, Sami, Juho-Pekka Virtanen, and Hannu Hyyppä. 2020. "A Simple Semantic-Based Data Storage Layout for Querying Point Clouds" ISPRS International Journal of Geo-Information 9, no. 2: 72. https://doi.org/10.3390/ijgi9020072
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