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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-08-01
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| 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 |
| _version_ | 1818566273541341184 |
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| author | K. Liu J. Boehm |
| author_facet | K. Liu J. Boehm |
| author_sort | K. Liu |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T01:51:35Z |
| format | Article |
| id | doaj.art-f64744fd4cf94b9db03d388cbd70c4a5 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-14T01:51:35Z |
| publishDate | 2015-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-f64744fd4cf94b9db03d388cbd70c4a52022-12-21T23:21:22ZengCopernicus 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 |
| 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 |
| title | 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_short | CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING |
| title_sort | classification of big point cloud data using cloud computing |
| 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 |