Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation
This paper is about road vehicle localisation based on vision using synthesised local orthographic imagery. We exploit state of the art stereo visual odometry (VO) on our survey vehicle to generate high precision synthetic orthographic images of the road surface as would be seen from overhead. The f...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
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2012
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| _version_ | 1797054553285197824 |
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| author | Napier, A Newman, P IEEE |
| author_facet | Napier, A Newman, P IEEE |
| author_sort | Napier, A |
| collection | OXFORD |
| description | This paper is about road vehicle localisation based on vision using synthesised local orthographic imagery. We exploit state of the art stereo visual odometry (VO) on our survey vehicle to generate high precision synthetic orthographic images of the road surface as would be seen from overhead. The fidelity and detail of these images far exceeds that of aerial photographs. When undertaking subsequent passes of the same route, the vehicle is localised against the survey vehicle's trajectory by maximising the mutual information between the synthetic orthographic images and live image streams. Thus we explicitly leverage the gross appearance of the workspace rather than a discrete set of point features. We test our technique on data gathered from a road vehicle and show that centimeter-level precision is possible without the complexity and instability of contemporary feature based techniques. © 2012 IEEE. |
| first_indexed | 2024-03-06T18:58:49Z |
| format | Journal article |
| id | oxford-uuid:12d229e5-1dfb-411f-8377-429007faec50 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:58:49Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oxford-uuid:12d229e5-1dfb-411f-8377-429007faec502022-03-26T10:10:15ZGeneration and Exploitation of Local Orthographic Imagery for Road Vehicle LocalisationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:12d229e5-1dfb-411f-8377-429007faec50EnglishSymplectic Elements at Oxford2012Napier, ANewman, PIEEEThis paper is about road vehicle localisation based on vision using synthesised local orthographic imagery. We exploit state of the art stereo visual odometry (VO) on our survey vehicle to generate high precision synthetic orthographic images of the road surface as would be seen from overhead. The fidelity and detail of these images far exceeds that of aerial photographs. When undertaking subsequent passes of the same route, the vehicle is localised against the survey vehicle's trajectory by maximising the mutual information between the synthetic orthographic images and live image streams. Thus we explicitly leverage the gross appearance of the workspace rather than a discrete set of point features. We test our technique on data gathered from a road vehicle and show that centimeter-level precision is possible without the complexity and instability of contemporary feature based techniques. © 2012 IEEE. |
| spellingShingle | Napier, A Newman, P IEEE Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation |
| title | Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation |
| title_full | Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation |
| title_fullStr | Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation |
| title_full_unstemmed | Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation |
| title_short | Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation |
| title_sort | generation and exploitation of local orthographic imagery for road vehicle localisation |
| work_keys_str_mv | AT napiera generationandexploitationoflocalorthographicimageryforroadvehiclelocalisation AT newmanp generationandexploitationoflocalorthographicimageryforroadvehiclelocalisation AT ieee generationandexploitationoflocalorthographicimageryforroadvehiclelocalisation |