Non-polyhedral landmark recognition using 3D depth images and partially correct models:
Abstract: "In this paper, we address the problem of modeling, recognising and localising non-polyhedral shapes or objects in partially known scenes, using 3D depth images. The applications this work aims at are mobile robotics for intervention or survey in environments like factories or nuclear...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Edinburgh
1995
|
| Schriftenreihe: | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper
752 |
| Schlagworte: | |
| Zusammenfassung: | Abstract: "In this paper, we address the problem of modeling, recognising and localising non-polyhedral shapes or objects in partially known scenes, using 3D depth images. The applications this work aims at are mobile robotics for intervention or survey in environments like factories or nuclear plants. This paper focusses on the problems of the recognition of non-polyhedral landmarks or objects and misplaced feature detection. In our approach, planes and some simplified classes of quadrics play an important part in the different processes. Surface classification takes into account the uncertainties on the measures and relies on probabilistic tests. The surface features belonging to those simplified classes provide a pose estimate which can be refined, if needed, using iconic methods. After registration, we compare the scene description and then a priori model for model validation and change detection." |
| Beschreibung: | [8] S. |
Internformat
MARC
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| 100 | 1 | |a Fillatreau, Philippe |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Non-polyhedral landmark recognition using 3D depth images and partially correct models |c Fillatreau, P. ; Fisher, R. B. |
| 264 | 1 | |a Edinburgh |c 1995 | |
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| 490 | 1 | |a University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |v 752 | |
| 520 | 3 | |a Abstract: "In this paper, we address the problem of modeling, recognising and localising non-polyhedral shapes or objects in partially known scenes, using 3D depth images. The applications this work aims at are mobile robotics for intervention or survey in environments like factories or nuclear plants. This paper focusses on the problems of the recognition of non-polyhedral landmarks or objects and misplaced feature detection. In our approach, planes and some simplified classes of quadrics play an important part in the different processes. Surface classification takes into account the uncertainties on the measures and relies on probabilistic tests. The surface features belonging to those simplified classes provide a pose estimate which can be refined, if needed, using iconic methods. After registration, we compare the scene description and then a priori model for model validation and change detection." | |
| 650 | 4 | |a Depth perception | |
| 650 | 4 | |a Mobile robots | |
| 650 | 4 | |a Robot vision | |
| 700 | 1 | |a Fisher, Robert B. |e Verfasser |4 aut | |
| 810 | 2 | |a Department of Artificial Intelligence: DAI research paper |t University <Edinburgh> |v 752 |w (DE-604)BV010450646 |9 752 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-007395261 | ||
Datensatz im Suchindex
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| any_adam_object | |
| author | Fillatreau, Philippe Fisher, Robert B. |
| author_facet | Fillatreau, Philippe Fisher, Robert B. |
| author_role | aut aut |
| author_sort | Fillatreau, Philippe |
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| building | Verbundindex |
| bvnumber | BV011044010 |
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| id | DE-604.BV011044010 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T18:03:04Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007395261 |
| oclc_num | 35073067 |
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| owner_facet | DE-91G DE-BY-TUM |
| physical | [8] S. |
| publishDate | 1995 |
| publishDateSearch | 1995 |
| publishDateSort | 1995 |
| record_format | marc |
| series2 | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |
| spelling | Fillatreau, Philippe Verfasser aut Non-polyhedral landmark recognition using 3D depth images and partially correct models Fillatreau, P. ; Fisher, R. B. Edinburgh 1995 [8] S. txt rdacontent n rdamedia nc rdacarrier University <Edinburgh> / Department of Artificial Intelligence: DAI research paper 752 Abstract: "In this paper, we address the problem of modeling, recognising and localising non-polyhedral shapes or objects in partially known scenes, using 3D depth images. The applications this work aims at are mobile robotics for intervention or survey in environments like factories or nuclear plants. This paper focusses on the problems of the recognition of non-polyhedral landmarks or objects and misplaced feature detection. In our approach, planes and some simplified classes of quadrics play an important part in the different processes. Surface classification takes into account the uncertainties on the measures and relies on probabilistic tests. The surface features belonging to those simplified classes provide a pose estimate which can be refined, if needed, using iconic methods. After registration, we compare the scene description and then a priori model for model validation and change detection." Depth perception Mobile robots Robot vision Fisher, Robert B. Verfasser aut Department of Artificial Intelligence: DAI research paper University <Edinburgh> 752 (DE-604)BV010450646 752 |
| spellingShingle | Fillatreau, Philippe Fisher, Robert B. Non-polyhedral landmark recognition using 3D depth images and partially correct models Depth perception Mobile robots Robot vision |
| title | Non-polyhedral landmark recognition using 3D depth images and partially correct models |
| title_auth | Non-polyhedral landmark recognition using 3D depth images and partially correct models |
| title_exact_search | Non-polyhedral landmark recognition using 3D depth images and partially correct models |
| title_full | Non-polyhedral landmark recognition using 3D depth images and partially correct models Fillatreau, P. ; Fisher, R. B. |
| title_fullStr | Non-polyhedral landmark recognition using 3D depth images and partially correct models Fillatreau, P. ; Fisher, R. B. |
| title_full_unstemmed | Non-polyhedral landmark recognition using 3D depth images and partially correct models Fillatreau, P. ; Fisher, R. B. |
| title_short | Non-polyhedral landmark recognition using 3D depth images and partially correct models |
| title_sort | non polyhedral landmark recognition using 3d depth images and partially correct models |
| topic | Depth perception Mobile robots Robot vision |
| topic_facet | Depth perception Mobile robots Robot vision |
| volume_link | (DE-604)BV010450646 |
| work_keys_str_mv | AT fillatreauphilippe nonpolyhedrallandmarkrecognitionusing3ddepthimagesandpartiallycorrectmodels AT fisherrobertb nonpolyhedrallandmarkrecognitionusing3ddepthimagesandpartiallycorrectmodels |