Keypoint-based 4-Points Congruent Sets – Automated marker-less registration of laser scans.
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| Title: | Keypoint-based 4-Points Congruent Sets – Automated marker-less registration of laser scans. |
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| Authors: | Theiler, Pascal Willy1 pascal.theiler@geod.baug.ethz.ch, Wegner, Jan Dirk1 jan.wegner@geod.baug.ethz.ch, Schindler, Konrad1 schindler@geod.baug.ethz.ch |
| Source: | ISPRS Journal of Photogrammetry & Remote Sensing. Oct2014, Vol. 96, p149-163. 15p. |
| Subjects: | Geometric congruences, Set theory, Automation, Optical scanners, Image registration, Data extraction |
| Abstract: | We propose a method to automatically register two point clouds acquired with a terrestrial laser scanner without placing any markers in the scene. What makes this task challenging are the strongly varying point densities caused by the line-of-sight measurement principle, and the huge amount of data. The first property leads to low point densities in potential overlap areas with scans taken from different viewpoints while the latter calls for highly efficient methods in terms of runtime and memory requirements. A crucial yet largely unsolved step is the initial coarse alignment of two scans without any simplifying assumptions, that is, point clouds are given in arbitrary local coordinates and no knowledge about their relative orientation is available. Once coarse alignment has been solved, scans can easily be fine-registered with standard methods like least-squares surface or Iterative Closest Point matching. In order to drastically thin out the original point clouds while retaining characteristic features, we resort to extracting 3D keypoints. Such clouds of keypoints, which can be viewed as a sparse but nevertheless discriminative representation of the original scans, are then used as input to a very efficient matching method originally developed in computer graphics, called 4-Points Congruent Sets (4PCS) algorithm. We adapt the 4PCS matching approach to better suit the characteristics of laser scans. The resulting Keypoint-based 4-Points Congruent Sets ( K-4PCS ) method is extensively evaluated on challenging indoor and outdoor scans. Beyond the evaluation on real terrestrial laser scans, we also perform experiments with simulated indoor scenes, paying particular attention to the sensitivity of the approach with respect to highly symmetric scenes. [ABSTRACT FROM AUTHOR] |
| Copyright of ISPRS Journal of Photogrammetry & Remote Sensing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 98141265 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Keypoint-based 4-Points Congruent Sets – Automated marker-less registration of laser scans. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Theiler%2C+Pascal+Willy%22">Theiler, Pascal Willy</searchLink><relatesTo>1</relatesTo><i> pascal.theiler@geod.baug.ethz.ch</i><br /><searchLink fieldCode="AR" term="%22Wegner%2C+Jan+Dirk%22">Wegner, Jan Dirk</searchLink><relatesTo>1</relatesTo><i> jan.wegner@geod.baug.ethz.ch</i><br /><searchLink fieldCode="AR" term="%22Schindler%2C+Konrad%22">Schindler, Konrad</searchLink><relatesTo>1</relatesTo><i> schindler@geod.baug.ethz.ch</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22ISPRS+Journal+of+Photogrammetry+%26+Remote+Sensing%22">ISPRS Journal of Photogrammetry & Remote Sensing</searchLink>. Oct2014, Vol. 96, p149-163. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Geometric+congruences%22">Geometric congruences</searchLink><br /><searchLink fieldCode="DE" term="%22Set+theory%22">Set theory</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+scanners%22">Optical scanners</searchLink><br /><searchLink fieldCode="DE" term="%22Image+registration%22">Image registration</searchLink><br /><searchLink fieldCode="DE" term="%22Data+extraction%22">Data extraction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We propose a method to automatically register two point clouds acquired with a terrestrial laser scanner without placing any markers in the scene. What makes this task challenging are the strongly varying point densities caused by the line-of-sight measurement principle, and the huge amount of data. The first property leads to low point densities in potential overlap areas with scans taken from different viewpoints while the latter calls for highly efficient methods in terms of runtime and memory requirements. A crucial yet largely unsolved step is the initial coarse alignment of two scans without any simplifying assumptions, that is, point clouds are given in arbitrary local coordinates and no knowledge about their relative orientation is available. Once coarse alignment has been solved, scans can easily be fine-registered with standard methods like least-squares surface or Iterative Closest Point matching. In order to drastically thin out the original point clouds while retaining characteristic features, we resort to extracting 3D keypoints. Such clouds of keypoints, which can be viewed as a sparse but nevertheless discriminative representation of the original scans, are then used as input to a very efficient matching method originally developed in computer graphics, called 4-Points Congruent Sets (4PCS) algorithm. We adapt the 4PCS matching approach to better suit the characteristics of laser scans. The resulting Keypoint-based 4-Points Congruent Sets ( K-4PCS ) method is extensively evaluated on challenging indoor and outdoor scans. Beyond the evaluation on real terrestrial laser scans, we also perform experiments with simulated indoor scenes, paying particular attention to the sensitivity of the approach with respect to highly symmetric scenes. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of ISPRS Journal of Photogrammetry & Remote Sensing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.isprsjprs.2014.06.015 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 149 Subjects: – SubjectFull: Geometric congruences Type: general – SubjectFull: Set theory Type: general – SubjectFull: Automation Type: general – SubjectFull: Optical scanners Type: general – SubjectFull: Image registration Type: general – SubjectFull: Data extraction Type: general Titles: – TitleFull: Keypoint-based 4-Points Congruent Sets – Automated marker-less registration of laser scans. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Theiler, Pascal Willy – PersonEntity: Name: NameFull: Wegner, Jan Dirk – PersonEntity: Name: NameFull: Schindler, Konrad IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2014 Type: published Y: 2014 Identifiers: – Type: issn-print Value: 09242716 Numbering: – Type: volume Value: 96 Titles: – TitleFull: ISPRS Journal of Photogrammetry & Remote Sensing Type: main |
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