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Classification of Big Point Cloud Data Using Cloud Computing

Liu, K; Boehm, J; (2015) Classification of Big Point Cloud Data Using Cloud Computing. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , XL-3/W pp. 553-557. 10.5194/isprsarchives-XL-3-W3-553-2015. Green open access

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Abstract

Point cloud data plays an significant role in various geospatial applications as it conveys plentiful information which can be used for different types of analysis. Semantic analysis, which is an important one of them, aims to label points as different categories. In machine learning, the problem is called classification. In addition, processing point data is becoming more and more challenging due to the growing data volume. In this paper, we address point data classification in a big data context. The popular cluster computing framework Apache Spark is used through the experiments and the promising results suggests a great potential of Apache Spark for large-scale point data processing.

Type: Article
Title: Classification of Big Point Cloud Data Using Cloud Computing
Open access status: An open access version is available from UCL Discovery
DOI: 10.5194/isprsarchives-XL-3-W3-553-2015
Publisher version: http://dx.doi.org/10.5194/isprsarchives-XL-3-W3-55...
Language: English
Additional information: © Author(s) 2015. This work is distributed under the Creative Commons Attribution 3.0 License.
Keywords: Point cloud, Machine learning, Cloud computing, Big data
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1471584
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