Relative pose estimation using image feature triplets

Show simple item record

dc.identifier.uri http://dx.doi.org/10.15488/875
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/899
dc.contributor.author Chuang, Tzu-Yi
dc.contributor.author Rottensteiner, Franz
dc.contributor.author Heipke, Christian
dc.date.accessioned 2016-12-16T10:43:04Z
dc.date.available 2016-12-16T10:43:04Z
dc.date.issued 2015
dc.identifier.citation Chuang, T.Y.; Rottensteiner, F.; Heipke, C.: Relative pose estimation using image feature triplets. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 40 (2015), Nr. 3W2, S. 39-45. DOI: https://doi.org/10.5194/isprsarchives-XL-3-W2-39-2015
dc.description.abstract A fully automated reconstruction of the trajectory of image sequences using point correspondences is turning into a routine practice. However, there are cases in which point features are hardly detectable, cannot be localized in a stable distribution, and consequently lead to an insufficient pose estimation. This paper presents a triplet-wise scheme for calibrated relative pose estimation from image point and line triplets, and investigates the effectiveness of the feature integration upon the relative pose estimation. To this end, we employ an existing point matching technique and propose a method for line triplet matching in which the relative poses are resolved during the matching procedure. The line matching method aims at establishing hypotheses about potential minimal line matches that can be used for determining the parameters of relative orientation (pose estimation) of two images with respect to the reference one; then, quantifying the agreement using the estimated orientation parameters. Rather than randomly choosing the line candidates in the matching process, we generate an associated lookup table to guide the selection of potential line matches. In addition, we integrate the homologous point and line triplets into a common adjustment procedure. In order to be able to also work with image sequences the adjustment is formulated in an incremental manner. The proposed scheme is evaluated with both synthetic and real datasets, demonstrating its satisfactory performance and revealing the effectiveness of image feature integration. eng
dc.language.iso eng
dc.publisher Hannover : International Society for Photogrammetry and Remote Sensing
dc.relation.ispartofseries International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 40 (2015), Nr. 3W2
dc.rights CC BY 3.0 Unported
dc.rights.uri http://creativecommons.org/licenses/by/3.0/
dc.subject Three-view geometry eng
dc.subject Computer vision eng
dc.subject Table lookup eng
dc.subject Feature integration eng
dc.subject Line triplet matching eng
dc.subject Matching process eng
dc.subject Orientation parameter eng
dc.subject Point correspondence eng
dc.subject Point matching tech-nique eng
dc.subject Relative orientation eng
dc.subject Three views eng
dc.subject Integration eng
dc.subject.classification Konferenzschrift ger
dc.subject.ddc 500 | Naturwissenschaften ger
dc.subject.ddc 530 | Physik ger
dc.title Relative pose estimation using image feature triplets eng
dc.type Article
dc.type Text
dc.relation.issn 16821750
dc.relation.doi https://doi.org/10.5194/isprsarchives-XL-3-W2-39-2015
dc.bibliographicCitation.issue 3W2
dc.bibliographicCitation.volume 40
dc.bibliographicCitation.firstPage 39
dc.bibliographicCitation.lastPage 45
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


Files in this item

This item appears in the following Collection(s):

Show simple item record

 

Search the repository


Browse

My Account

Usage Statistics