Using depth maps to find interesting regions
Automated recognition and analysis of objects in images from urban transport corridors are important for many applications including asset management, measurement, location, analysis and change detection. Vehicle-based mobile mapping systems capture co-registered imagery and 3D point cloud informati...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Institute of Electrical and Electronics Engineers Inc
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/15163 |
| _version_ | 1848748819083165696 |
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| author | Borck, Michael Palmer, Richard West, Geoff Tan, Tele |
| author2 | IEEE Editorial Board |
| author_facet | IEEE Editorial Board Borck, Michael Palmer, Richard West, Geoff Tan, Tele |
| author_sort | Borck, Michael |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Automated recognition and analysis of objects in images from urban transport corridors are important for many applications including asset management, measurement, location, analysis and change detection. Vehicle-based mobile mapping systems capture co-registered imagery and 3D point cloud information over hundreds of kilometers of transport corridor. Methods for extracting information from these large datasets are labour intensive and automatic methods are desired. This paper uses a depth map to segment regions of interest in colour images. Quantitative tests were carried out on two datasets. Experiments show that the resulting regions are relatively coarse, but overall the method is effective, and has the benefit of easy implementation. |
| first_indexed | 2025-11-14T07:11:06Z |
| format | Conference Paper |
| id | curtin-20.500.11937-15163 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:11:06Z |
| publishDate | 2014 |
| publisher | Institute of Electrical and Electronics Engineers Inc |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-151632017-09-13T15:04:45Z Using depth maps to find interesting regions Borck, Michael Palmer, Richard West, Geoff Tan, Tele IEEE Editorial Board Automated recognition and analysis of objects in images from urban transport corridors are important for many applications including asset management, measurement, location, analysis and change detection. Vehicle-based mobile mapping systems capture co-registered imagery and 3D point cloud information over hundreds of kilometers of transport corridor. Methods for extracting information from these large datasets are labour intensive and automatic methods are desired. This paper uses a depth map to segment regions of interest in colour images. Quantitative tests were carried out on two datasets. Experiments show that the resulting regions are relatively coarse, but overall the method is effective, and has the benefit of easy implementation. 2014 Conference Paper http://hdl.handle.net/20.500.11937/15163 10.1109/TENCONSpring.2014.6862998 Institute of Electrical and Electronics Engineers Inc restricted |
| spellingShingle | Borck, Michael Palmer, Richard West, Geoff Tan, Tele Using depth maps to find interesting regions |
| title | Using depth maps to find interesting regions |
| title_full | Using depth maps to find interesting regions |
| title_fullStr | Using depth maps to find interesting regions |
| title_full_unstemmed | Using depth maps to find interesting regions |
| title_short | Using depth maps to find interesting regions |
| title_sort | using depth maps to find interesting regions |
| url | http://hdl.handle.net/20.500.11937/15163 |