Learning Hierarchical Semantic Segmentations of LIDAR Data
Author(s): Dohan, David; Matejek, Brian; Funkhouser, Thomas
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Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dohan, David | - |
dc.contributor.author | Matejek, Brian | - |
dc.contributor.author | Funkhouser, Thomas | - |
dc.date.accessioned | 2021-10-08T19:46:29Z | - |
dc.date.available | 2021-10-08T19:46:29Z | - |
dc.date.issued | 2015 | en_US |
dc.identifier.citation | Dohan, David, Brian Matejek, and Thomas Funkhouser. "Learning Hierarchical Semantic Segmentations of LIDAR Data." In International Conference on 3D Vision (2015): pp. 273-281. doi:10.1109/3DV.2015.38 | en_US |
dc.identifier.uri | https://www.cs.princeton.edu/~funk/3DV15.pdf | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/pr1qg08 | - |
dc.description.abstract | This paper investigates a method for semantic segmentation of small objects in terrestrial LIDAR scans in urban environments. The core research contribution is a hierarchical segmentation algorithm where potential merges between segments are prioritized by a learned affinity function and constrained to occur only if they achieve a significantly high object classification probability. This approach provides a way to integrate a learned shape-prior (the object classifier) into a search for the best semantic segmentation in a fast and practical algorithm. Experiments with LIDAR scans collected by Google Street View cars throughout ~100 city blocks of New York City show that the algorithm provides better segmentations and classifications than simple alternatives for cars, vans, traffic lights, and street lights. | en_US |
dc.format.extent | 273 - 281 | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartof | International Conference on 3D Vision | en_US |
dc.rights | Author's manuscript | en_US |
dc.title | Learning Hierarchical Semantic Segmentations of LIDAR Data | en_US |
dc.type | Conference Article | en_US |
dc.identifier.doi | 10.1109/3DV.2015.38 | - |
pu.type.symplectic | http://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceeding | en_US |
Files in This Item:
File | Description | Size | Format | |
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HierarchicalSemanticSegmentationLidarData.pdf | 1.35 MB | Adobe PDF | View/Download |
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