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 |
| Published: |
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 |
| Summary: | 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. |
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| ISSN: | 2194-9042 2194-9050 |