Intensity and Range Based Features for Object Detection in Mobile Mapping Data
Mobile mapping is used for asset management, change detection, surveying and dimensional analysis. There is a great desire to automate these processes given the very large amounts of data, especially when 3-D point cloud data is combined with co-registered imagery - termed “3-D images”. One approach...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
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Copernicus GmbH
2012
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| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/ http://hdl.handle.net/20.500.11937/32182 |
| _version_ | 1848753590411198464 |
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| author | Palmer, Richard Borck, Michael West, Geoff Tan, Tele |
| author2 | M. Shortis |
| author_facet | M. Shortis Palmer, Richard Borck, Michael West, Geoff Tan, Tele |
| author_sort | Palmer, Richard |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Mobile mapping is used for asset management, change detection, surveying and dimensional analysis. There is a great desire to automate these processes given the very large amounts of data, especially when 3-D point cloud data is combined with co-registered imagery - termed “3-D images”. One approach requires low-level feature extraction from the images and point cloud data followed by pattern recognition and machine learning techniques to recognise the various high level features (or objects) in the images. This paper covers low-level feature analysis and investigates a number of different feature extraction methods for their usefulness. The features of interest include those based on the “bag of words” concept in which many low-level features are used e.g. histograms of gradients, as well as those describing the saliency (how unusual a region of the image is). These mainly image based features have been adapted to deal with 3-D images. The performance of the various features are discussed for typical mobile mapping scenarios and recommendations made as to the best features to use. |
| first_indexed | 2025-11-14T08:26:56Z |
| format | Conference Paper |
| id | curtin-20.500.11937-32182 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:26:56Z |
| publishDate | 2012 |
| publisher | Copernicus GmbH |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-321822023-02-07T08:01:19Z Intensity and Range Based Features for Object Detection in Mobile Mapping Data Palmer, Richard Borck, Michael West, Geoff Tan, Tele M. Shortis N. Paparoditis C. Mallet Mobile mapping is used for asset management, change detection, surveying and dimensional analysis. There is a great desire to automate these processes given the very large amounts of data, especially when 3-D point cloud data is combined with co-registered imagery - termed “3-D images”. One approach requires low-level feature extraction from the images and point cloud data followed by pattern recognition and machine learning techniques to recognise the various high level features (or objects) in the images. This paper covers low-level feature analysis and investigates a number of different feature extraction methods for their usefulness. The features of interest include those based on the “bag of words” concept in which many low-level features are used e.g. histograms of gradients, as well as those describing the saliency (how unusual a region of the image is). These mainly image based features have been adapted to deal with 3-D images. The performance of the various features are discussed for typical mobile mapping scenarios and recommendations made as to the best features to use. 2012 Conference Paper http://hdl.handle.net/20.500.11937/32182 http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/ Copernicus GmbH restricted |
| spellingShingle | Palmer, Richard Borck, Michael West, Geoff Tan, Tele Intensity and Range Based Features for Object Detection in Mobile Mapping Data |
| title | Intensity and Range Based Features for Object Detection in Mobile Mapping Data |
| title_full | Intensity and Range Based Features for Object Detection in Mobile Mapping Data |
| title_fullStr | Intensity and Range Based Features for Object Detection in Mobile Mapping Data |
| title_full_unstemmed | Intensity and Range Based Features for Object Detection in Mobile Mapping Data |
| title_short | Intensity and Range Based Features for Object Detection in Mobile Mapping Data |
| title_sort | intensity and range based features for object detection in mobile mapping data |
| url | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/ http://hdl.handle.net/20.500.11937/32182 |