Point cloud databases

László Dobos, I. Csabai, János M. Szalai-Gindl, Tamás Budavári, Alexander S. Szalay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We introduce the concept of the point cloud database, a new kind of database system aimed primarily towards scientific applications. Many scientific observations, experiments, feature extraction algorithms and large-scale simulations produce enormous amounts of data that are better represented as sparse (but often highly-clustered) points in a k-dimensional (κ ≲ 10) metric space than on a multidimensional grid. Dimensionality reduction techniques, such as principal components, are also widely-used to project high dimensional data into similarly low dimensional spaces. Analysis techniques developed to work on multi-dimensional data points are usually implemented as in-memory algorithms and need to be modified to work in distributed cluster environments and on large amounts of disk-resident data. We conclude that the relational model, with certain additions, is appropriate for point clouds, but point cloud databases must also provide unique set of spatial search and proximity join operators, indexing schemes, and query language constructs that make them a distinct class of database systems.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
ISBN (Print)9781450327220
DOIs
Publication statusPublished - 2014
Event26th International Conference on Scientific and Statistical Database Management, SSDBM 2014 - Aalborg, Denmark
Duration: Jun 30 2014Jul 2 2014

Other

Other26th International Conference on Scientific and Statistical Database Management, SSDBM 2014
CountryDenmark
CityAalborg
Period6/30/147/2/14

Fingerprint

Query languages
Feature extraction
Data storage equipment
Experiments

Keywords

  • Multi-dimensional database
  • Proximity join
  • Spatial indexing

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Dobos, L., Csabai, I., Szalai-Gindl, J. M., Budavári, T., & Szalay, A. S. (2014). Point cloud databases. In ACM International Conference Proceeding Series [33] Association for Computing Machinery. https://doi.org/10.1145/2618243.2618275

Point cloud databases. / Dobos, László; Csabai, I.; Szalai-Gindl, János M.; Budavári, Tamás; Szalay, Alexander S.

ACM International Conference Proceeding Series. Association for Computing Machinery, 2014. 33.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Dobos, L, Csabai, I, Szalai-Gindl, JM, Budavári, T & Szalay, AS 2014, Point cloud databases. in ACM International Conference Proceeding Series., 33, Association for Computing Machinery, 26th International Conference on Scientific and Statistical Database Management, SSDBM 2014, Aalborg, Denmark, 6/30/14. https://doi.org/10.1145/2618243.2618275
Dobos L, Csabai I, Szalai-Gindl JM, Budavári T, Szalay AS. Point cloud databases. In ACM International Conference Proceeding Series. Association for Computing Machinery. 2014. 33 https://doi.org/10.1145/2618243.2618275
Dobos, László ; Csabai, I. ; Szalai-Gindl, János M. ; Budavári, Tamás ; Szalay, Alexander S. / Point cloud databases. ACM International Conference Proceeding Series. Association for Computing Machinery, 2014.
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