A Simple Semantic-Based Data Storage Layout for Querying Point Clouds

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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.
Original languageEnglish
Article number9020072
Number of pages28
JournalISPRS International Journal of Geo-Information
Issue number2
Publication statusPublished - 22 Jan 2020
MoE publication typeA1 Journal article-refereed


  • point cloud
  • LiDAR
  • semantic class
  • point cloud database
  • NoSQL
  • Python


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