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Auteur Horst Wildenauer |
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Structure from motion with line segments under relaxed endpoint constraints / Branislav Micusik in International journal of computer vision, vol 124 n° 1 (August 2017)
[article]
Titre : Structure from motion with line segments under relaxed endpoint constraints Type de document : Article/Communication Auteurs : Branislav Micusik, Auteur ; Horst Wildenauer, Auteur Année de publication : 2017 Article en page(s) : pp 65 – 79 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image numérique
[Termes IGN] appariement de lignes
[Termes IGN] carte d'intérieur
[Termes IGN] compensation par faisceaux
[Termes IGN] géométrie épipolaire
[Termes IGN] programmation par contraintes
[Termes IGN] segment de droite
[Termes IGN] segmentation d'image
[Termes IGN] structure-from-motion
[Termes IGN] translationRésumé : (auteur) We present a novel structure from motion pipeline, which estimates motion and wiry 3D structure from imaged line segments across multiple views. Although the position and orientation of line segments can be determined more accurately than point features, the instability of their endpoints and the fact that lines are not constrained by epipolar geometry diverted most research focus away to point-based methods. In our approach, we tackle the problem of instable endpoints by utilizing relaxed constraints on their positions, both during matching and as well in the following bundle adjustment stage. Furthermore, we gain efficiency in estimating trifocal image relations by decoupling rotation and translation. To this end, a novel linear solver for relative translation estimation given rotations from five line correspondences in three views is introduced. Extensive experiments on long image sequences show that our line-based structure from motion pipeline advantageously complements point-based methods, giving more meaningful 3D representation for indoor scenarios. Numéro de notice : A2017-400 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007%2Fs11263-016-0971-9 En ligne : https://doi.org/10.1007/s11263-016-0971-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85942
in International journal of computer vision > vol 124 n° 1 (August 2017) . - pp 65 – 79[article]