Abstract
This paper focusses on the feasibility of classifiers, developed for classifying multispectral images, for assigning classes to point clouds of urban scenes. The motivation of our research is that dense point clouds require fast classification methods to extract meaningful information within a reasonable amount of time and multispectral classifiers do have this property. We employ two encoding methods acting on one feature: the altitude above street level. We emphasize computation time and therefore we use just one feature in this prelimina
Original language | English |
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Title of host publication | Proceedings of the 20th AGILE Conference on Geographic Information Science |
Subtitle of host publication | Societal Geo-innovation |
Editors | Arnold Bregt, Tapani Sarjakoski, Ron van Lammeren, Frans Rip |
Publisher | Wageningen University |
Number of pages | 2 |
ISBN (Electronic) | 978-90-816960-7-4 |
Publication status | Published - 2017 |
Event | AGILE 2017: 20th AGILE International Conference on Geographic Information Science - Wageningen, Netherlands Duration: 9 May 2017 → 12 May 2017 https://agile-online.org/index.php/conference/conference-2017 |
Conference
Conference | AGILE 2017: 20th AGILE International Conference on Geographic Information Science |
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Country/Territory | Netherlands |
City | Wageningen |
Period | 9/05/17 → 12/05/17 |
Internet address |
Keywords
- Classification
- point clouds
- feature encoding