Wientapper, Folker ; Kuijper, Arjan (2017)
Unifying Algebraic Solvers for Scaled Euclidean Registration from Point, Line and Plane Constraints.
Taipei, Taiwan (20.11.2016-24.11.2016)
doi: 10.1007/978-3-319-54193-8_4
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We investigate recent state-of-the-art algorithms for absolute pose problems (PnP and GPnP) and analyse their applicability to a more general type, namely the scaled Euclidean registration from pointto- point, point-to-line and point-to plane correspondences. Similar to previous formulations we first compress the original set of equations to a least squares error function that only depends on the non-linear rotation parameters and a small symmetric coefficient matrix of fixed size. Then, in a second step the rotation is solved with algorithms which are derived using methods from algebraic geometry such as the Gröbner basis method. In previous approaches the first compression step was usually tailored to a specific correspondence types and problem instances. Here, we propose a unified formulation based on a representation with orthogonal complements which allows to combine different types of constraints elegantly in one single framework. We show that with our unified formulation existing polynomial solvers can be interchangeably applied to problem instances other than those they were originally proposed for. It becomes possible to compare them on various registrations problems with respect to accuracy, numerical stability, and computational speed. Our compression procedure not only preserves linear complexity, it is even faster than previous formulations. For the second step we also derive an own algebraic equation solver, which can additionally handle the registration from 3D point-to-point correspondences, where other solvers surprisingly fail.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2017 |
Autor(en): | Wientapper, Folker ; Kuijper, Arjan |
Art des Eintrags: | Bibliographie |
Titel: | Unifying Algebraic Solvers for Scaled Euclidean Registration from Point, Line and Plane Constraints |
Sprache: | Englisch |
Publikationsjahr: | 2017 |
Ort: | Berlin |
Verlag: | Springer |
Buchtitel: | Computer Vision – ACCV 2016 : rev. selected papers, Pt V |
Veranstaltungsort: | Taipei, Taiwan |
Veranstaltungsdatum: | 20.11.2016-24.11.2016 |
DOI: | 10.1007/978-3-319-54193-8_4 |
URL / URN: | https://doi.org/10.1007/978-3-319-54193-8_4 |
Kurzbeschreibung (Abstract): | We investigate recent state-of-the-art algorithms for absolute pose problems (PnP and GPnP) and analyse their applicability to a more general type, namely the scaled Euclidean registration from pointto- point, point-to-line and point-to plane correspondences. Similar to previous formulations we first compress the original set of equations to a least squares error function that only depends on the non-linear rotation parameters and a small symmetric coefficient matrix of fixed size. Then, in a second step the rotation is solved with algorithms which are derived using methods from algebraic geometry such as the Gröbner basis method. In previous approaches the first compression step was usually tailored to a specific correspondence types and problem instances. Here, we propose a unified formulation based on a representation with orthogonal complements which allows to combine different types of constraints elegantly in one single framework. We show that with our unified formulation existing polynomial solvers can be interchangeably applied to problem instances other than those they were originally proposed for. It becomes possible to compare them on various registrations problems with respect to accuracy, numerical stability, and computational speed. Our compression procedure not only preserves linear complexity, it is even faster than previous formulations. For the second step we also derive an own algebraic equation solver, which can additionally handle the registration from 3D point-to-point correspondences, where other solvers surprisingly fail. |
Freie Schlagworte: | 3D Computer vision, Optimization, Algebraic geometry, Registration, Pose estimation |
Zusätzliche Informationen: | Lecture Notes in Computer Science, vol 10115 |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
Hinterlegungsdatum: | 05 Mai 2020 14:52 |
Letzte Änderung: | 05 Mai 2020 14:52 |
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