CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING

CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING

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...

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Bibliographic Details
Main Authors: K. Liu, J. Boehm
Format: Article
Language:English
Published: Copernicus Publications 2015-08-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/553/2015/isprsarchives-XL-3-W3-553-2015.pdf
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spelling doaj-f64744fd4cf94b9db03d388cbd70c4a52020-11-24T21:15:21ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342015-08-01XL-3/W355355710.5194/isprsarchives-XL-3-W3-553-2015CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTINGK. Liu0J. Boehm1Dept of Civil, Environ & Geomatic Eng, University College London, UKDept of Civil, Environ & Geomatic Eng, University College London, UKPoint 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.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/553/2015/isprsarchives-XL-3-W3-553-2015.pdf
collection DOAJ
language English
format Article
sources DOAJ
author K. Liu
J. Boehm
spellingShingle K. Liu
J. Boehm
CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet K. Liu
J. Boehm
author_sort K. Liu
title CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING
title_short CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING
title_full CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING
title_fullStr CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING
title_full_unstemmed CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING
title_sort classification of big point cloud data using cloud computing
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2015-08-01
description 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.
url http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W3/553/2015/isprsarchives-XL-3-W3-553-2015.pdf
work_keys_str_mv AT kliu classificationofbigpointclouddatausingcloudcomputing
AT jboehm classificationofbigpointclouddatausingcloudcomputing
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