PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATA
Many industrial applications require dense point clouds of the installations. Acquisition of the rooms, filled with many objects, of an industrial scene leads to many Terrestrial Laser Scanner (TLS) stations. A precise registration of all the per-station point clouds is crucial for the required ac...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2012-07-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-3/221/2012/isprsannals-I-3-221-2012.pdf |
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| author | J.-F. Hullo J.-F. Hullo G. Thibault G. Thibault P. Grussenmeyer T. Landes D. Bennequin |
| author_facet | J.-F. Hullo J.-F. Hullo G. Thibault G. Thibault P. Grussenmeyer T. Landes D. Bennequin |
| author_sort | J.-F. Hullo |
| collection | DOAJ |
| description | Many industrial applications require dense point clouds of the installations. Acquisition of the rooms, filled with many objects, of an
industrial scene leads to many Terrestrial Laser Scanner (TLS) stations. A precise registration of all the per-station point clouds is crucial
for the required accuracy of 1-2 cm of final data. Targets and tachometry, current best practice for registration, slows down the survey
and limits the number of campaigns. Indoor geolocation system are faster but do not reach the final required accuracy. Otherwise, 3D
primitives can be automatically extracted from the dense point clouds and possibly used for registration. In a four step primitive-based
registration, Acquisition – Reconstruction – Matching – Solving, the matching is crucial. This article presents a probabilistic test for 3D
lines matching using <i>a priori</i> distributions of approximated transformations. The stochastic model of approximated transformations
and resulting uncertain lines is introduced. A test is performed on a real dataset of an industrial scene and the results are analysed.
Improvements of the presented test and matching framework are also discussed. |
| first_indexed | 2024-04-13T03:47:49Z |
| format | Article |
| id | doaj.art-47e9de90f5ff48b2b175a90d15a435af |
| institution | Directory Open Access Journal |
| issn | 2194-9042 2194-9050 |
| language | English |
| last_indexed | 2024-04-13T03:47:49Z |
| publishDate | 2012-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-47e9de90f5ff48b2b175a90d15a435af2022-12-22T03:03:56ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502012-07-01I-322122610.5194/isprsannals-I-3-221-2012PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATAJ.-F. Hullo0J.-F. Hullo1G. Thibault2G. Thibault3P. Grussenmeyer4T. Landes5D. Bennequin6SINETICS I2C, EDF R&D, 92140 Clamart, FranceThe Image Sciences, Computer Sciences and Remote Sensing Laboratory, LSIIT-TRIO UMR 7005, INSA Strasbourg, FranceSINETICS I2C, EDF R&D, 92140 Clamart, FranceLaboratoire de Physiologie de la Perception et de l'Action, Colège de France, UMR 7152, CNRS, Paris, FranceThe Image Sciences, Computer Sciences and Remote Sensing Laboratory, LSIIT-TRIO UMR 7005, INSA Strasbourg, FranceThe Image Sciences, Computer Sciences and Remote Sensing Laboratory, LSIIT-TRIO UMR 7005, INSA Strasbourg, FranceÉquipe Géométrie et Dynamique, Institut de Mathématiques de Jussieu, UMR 7586, Paris, FranceMany industrial applications require dense point clouds of the installations. Acquisition of the rooms, filled with many objects, of an industrial scene leads to many Terrestrial Laser Scanner (TLS) stations. A precise registration of all the per-station point clouds is crucial for the required accuracy of 1-2 cm of final data. Targets and tachometry, current best practice for registration, slows down the survey and limits the number of campaigns. Indoor geolocation system are faster but do not reach the final required accuracy. Otherwise, 3D primitives can be automatically extracted from the dense point clouds and possibly used for registration. In a four step primitive-based registration, Acquisition – Reconstruction – Matching – Solving, the matching is crucial. This article presents a probabilistic test for 3D lines matching using <i>a priori</i> distributions of approximated transformations. The stochastic model of approximated transformations and resulting uncertain lines is introduced. A test is performed on a real dataset of an industrial scene and the results are analysed. Improvements of the presented test and matching framework are also discussed.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-3/221/2012/isprsannals-I-3-221-2012.pdf |
| spellingShingle | J.-F. Hullo J.-F. Hullo G. Thibault G. Thibault P. Grussenmeyer T. Landes D. Bennequin PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATA ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATA |
| title_full | PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATA |
| title_fullStr | PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATA |
| title_full_unstemmed | PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATA |
| title_short | PROBABILISTIC FEATURE MATCHING APPLIED TO PRIMITIVE BASED REGISTRATION OF TLS DATA |
| title_sort | probabilistic feature matching applied to primitive based registration of tls data |
| url | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-3/221/2012/isprsannals-I-3-221-2012.pdf |
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