Centre de documentation
scientifique

Parallax-tolerant aerial image georegistration and efficient camera pose refinement—without piecewise homographies / Hadi AliAkbarpour in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4618 - 4637 Titre : Parallax-tolerant aerial image georegistration and efficient camera pose refinement—without piecewise homographies Type de document : Article/Communication Auteurs : Hadi AliAkbarpour, Auteur ; Kannappan Palaniappan, Auteur ; Guna Seetharaman, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 4618 - 4637 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] bruit (théorie du signal) [Termes IGN] caméra numérique [Termes IGN] compensation par faisceaux [Termes IGN] décomposition d'image [Termes IGN] géoréférencement [Termes IGN] image aérienne [Termes IGN] métadonnées [Termes IGN] orthorectification [Termes IGN] reconstruction 3D [Termes IGN] structure-from-motion Résumé : (Auteur) We describe a fast and efficient camera pose refinement and Structure from Motion (SfM) method for sequential aerial imagery with applications to georegistration and 3-D reconstruction. Inputs to the system are 2-D images combined with initial noisy camera metadata measurements, available from on-board sensors (e.g., camera, global positioning system, and inertial measurement unit). Georegistration is required to stabilize the ground-plane motion to separate camera-induced motion from object motion to support vehicle tracking in aerial imagery. In the proposed approach, we recover accurate camera pose and (sparse) 3-D structure using bundle adjustment for sequential imagery (BA4S) and then stabilize the video from the moving platform by analytically solving for the image-plane-to-ground-plane homography transformation. Using this approach, we avoid relying upon image-to-image registration, which requires estimating feature correspondences (i.e., matching) followed by warping between images (in a 2-D space) that is an error prone process for complex scenes with parallax, appearance, and illumination changes. Both our SfM (BA4S) and our analytical ground-plane georegistration method avoid the use of iterative consensus combinatorial methods like RANdom SAmple Consensus which is a core part of many published approaches. BA4S is very efficient for long sequential imagery and is more than 130 times faster than VisualSfM, 35 times faster than MavMap, and about 274 times faster than Pix4D. Various experimental results demonstrate the efficiency and robustness of the proposed pipeline for the refinement of camera parameters in sequential aerial imagery and georegistration. Numéro de notice : A2017-501 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2695172 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2695172 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86444 [article]