Monocular Template-Based Reconstruction of Smooth and Inextensible Surfaces
Identifieur interne : 002F21 ( Istex/Curation ); précédent : 002F20; suivant : 002F22Monocular Template-Based Reconstruction of Smooth and Inextensible Surfaces
Auteurs : Florent Brunet [France, Allemagne] ; Richard Hartley [Australie] ; Adrien Bartoli [France] ; Nassir Navab [Allemagne] ; Remy Malgouyres [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2011.
English descriptors
- KwdEn :
- Algorithm, Approach ffdref, Bartoli, Brunet, Computer vision, Constraint, Convex, Convex formulation, Cost function, Data points, Data term, Deformable, Deformable surfaces, Deformed paths, Euclidean, Euclidean distance, Ffdinit, Ffdref, Gaussian, Gaussian curvature, Geodesic, Geodesic distance, Gure, Ieee, Ieee conference, Ieee transactions, Inextensibility, Inextensibility constraint, Inextensibility constraints, Inextensible, Inextensible surface, Inextensible surfaces, Initial solution, Input image, Input images, Jacobian matrix, Local isometry, Matrix, Minimization, Minimization problem, Monocular, Monocular reconstruction, Pattern recognition, Perspective camera, Point correspondences, Possible surfaces, Real data, Reconstructed, Reconstructed surface, Reconstruction algorithm, Reference shape, Reprojection, Reprojection error, Smooth surface, Smooth surfaces, Socp, Socp problem, Stereo reconstruction, Surface model, Template, Template image, Template image space.
- Teeft :
- Algorithm, Approach ffdref, Bartoli, Brunet, Computer vision, Constraint, Convex, Convex formulation, Cost function, Data points, Data term, Deformable, Deformable surfaces, Deformed paths, Euclidean, Euclidean distance, Ffdinit, Ffdref, Gaussian, Gaussian curvature, Geodesic, Geodesic distance, Gure, Ieee, Ieee conference, Ieee transactions, Inextensibility, Inextensibility constraint, Inextensibility constraints, Inextensible, Inextensible surface, Inextensible surfaces, Initial solution, Input image, Input images, Jacobian matrix, Local isometry, Matrix, Minimization, Minimization problem, Monocular, Monocular reconstruction, Pattern recognition, Perspective camera, Point correspondences, Possible surfaces, Real data, Reconstructed, Reconstructed surface, Reconstruction algorithm, Reference shape, Reprojection, Reprojection error, Smooth surface, Smooth surfaces, Socp, Socp problem, Stereo reconstruction, Surface model, Template, Template image, Template image space.
Abstract
Abstract: We present different approaches to reconstructing an inextensible surface from point correspondences between an input image and a template image representing a flat reference shape from a fronto-parallel point of view. We first propose a ‘point-wise’ method, i.e. a method that only retrieves the 3D positions of the point correspondences. This method is formulated as a second-order cone program and it handles inaccuracies in the point measurements. It relies on the fact that the Euclidean distance between two 3D points must be shorter than their geodesic distance (which can easily be computed from the template image). We then present an approach that reconstructs a smooth 3D surface based on Free-Form Deformations. The surface is represented as a smooth map from the template image space to the 3D space. Our idea is to say that the 2D-3D map must be everywhere a local isometry. This induces conditions on the Jacobian matrix of the map which are included in a least-squares minimization problem.
Url:
DOI: 10.1007/978-3-642-19318-7_5
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<front><div type="abstract" xml:lang="en">Abstract: We present different approaches to reconstructing an inextensible surface from point correspondences between an input image and a template image representing a flat reference shape from a fronto-parallel point of view. We first propose a ‘point-wise’ method, i.e. a method that only retrieves the 3D positions of the point correspondences. This method is formulated as a second-order cone program and it handles inaccuracies in the point measurements. It relies on the fact that the Euclidean distance between two 3D points must be shorter than their geodesic distance (which can easily be computed from the template image). We then present an approach that reconstructs a smooth 3D surface based on Free-Form Deformations. The surface is represented as a smooth map from the template image space to the 3D space. Our idea is to say that the 2D-3D map must be everywhere a local isometry. This induces conditions on the Jacobian matrix of the map which are included in a least-squares minimization problem.</div>
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