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Automatic sensor orientation using horizontal and vertical line feature constraints / Yanbiao Sun in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 172 - 184 Titre : Automatic sensor orientation using horizontal and vertical line feature constraints Type de document : Article/Communication Auteurs : Yanbiao Sun, Auteur ; Stuart Robson, Auteur ; Daniel Scott, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 172 - 184 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] angle azimutal [Termes IGN] angle vertical [Termes IGN] compensation par faisceaux [Termes IGN] coordonnées horizontales [Termes IGN] extraction de traits caractéristiques [Termes IGN] forme linéaire [Termes IGN] image aérienne [Termes IGN] ligne caractéristique [Termes IGN] orientation d'image [Termes IGN] orientation du capteur [Termes IGN] point d'appui Résumé : (Auteur) To improve the accuracy of sensor orientation using calibrated aerial images, this paper proposes an automatic sensor orientation method utilizing horizontal and vertical constraints on human-engineered structures, addressing the limitations faced with sub-optimal number of Ground Control Points (GCPs) within a scene. Related state-of-the-art methods rely on structured building edges, and necessitate manual identification of end points. Our method makes use of line-segments but eliminates the need for these matched end points, thus eliminating the need for inefficient manual intervention. To achieve this, a 3D line in object space is represented by the intersection of two planes going through two camera centers. The normal vector of each plane can be written as a function of a pair of azimuth and elevations angles. The normal vector of the 3D line can be expressed by the cross product of these two plane’s normal vectors. Then, we create observation functions of horizontal and vertical line constraints based on the zero-vector cross-product and the dot-product of the normal vector of the 3D lines. The observation functions of the horizontal and vertical lines are then introduced into a hybrid Bundle Adjustment (BA) method as constraints, including observed image points as well as observed line segment projections. Finally, to assess the feasibility and effectiveness of the proposed method, simulated and real data are tested. The results demonstrate that, in cases with only 3 GCPs, the accuracy of the proposed method utilizing line features extracted automatically, is increased by 50%, compared to a BA using only point constraints. Numéro de notice : A2019-140 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.011 Date de publication en ligne : 28/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.011 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92478 [article]

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