Software

The Globally-Optimal Pose And Correspondences (GOPAC) Algorithm

Commonwealth Scientific and Industrial Research Organisation

Campbell, Dylan ; Petersson, Lars ; Kneip, Laurent ; Li, Hongdong

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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/08/5b2b4c9874fd9&rft.title=The Globally-Optimal Pose And Correspondences (GOPAC) Algorithm&rft.identifier=https://doi.org/10.4225/08/5b2b4c9874fd9&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=A globally-optimal inlier set cardinality maximisation algorithm that jointly estimates optimal camera pose and optimal correspondences. The approach employs branch-and-bound to search the 6D space of camera poses, guaranteeing global optimality without requiring a pose prior. The geometry of SE(3) is used to find novel upper and lower bounds for the number of inliers and local optimisation is integrated to accelerate convergence.Lineage: Source code accompanying the publications of a TPAMI journal article and a conference paper at the 2017 International Conference on Computer Vision (see Credit).&rft.creator=Campbell, Dylan &rft.creator=Petersson, Lars &rft.creator=Kneip, Laurent &rft.creator=Li, Hongdong &rft.date=2018&rft.edition=v2&rft.relation=https://ieeexplore.ieee.org/document/8388302&rft.relation=https://ieeexplore.ieee.org/document/8237272&rft_rights=GPLv3 Licence with CSIRO Disclaimer https://research.csiro.au/dap/licences/gplv3-licence-with-csiro-disclaimer/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2018.&rft_subject=globally-optimal&rft_subject=GOPAC&rft_subject=camera pose estimation&rft_subject=2D-3D registration&rft_subject=image alignment and registration&rft_subject=calibration and pose estimation&rft_subject=vision for robotics&rft_subject=3D modelling and reconstruction&rft_subject=Computer vision&rft_subject=Computer vision and multimedia computation&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft.type=Computer Program&rft.language=English Access the software

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GPLv3 Licence with CSIRO Disclaimer
https://research.csiro.au/dap/licences/gplv3-licence-with-csiro-disclaimer/

Data is accessible online and may be reused in accordance with licence conditions

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A globally-optimal inlier set cardinality maximisation algorithm that jointly estimates optimal camera pose and optimal correspondences. The approach employs branch-and-bound to search the 6D space of camera poses, guaranteeing global optimality without requiring a pose prior. The geometry of SE(3) is used to find novel upper and lower bounds for the number of inliers and local optimisation is integrated to accelerate convergence.
Lineage: Source code accompanying the publications of a TPAMI journal article and a conference paper at the 2017 International Conference on Computer Vision (see Credit).

Available: 2018-06-21

Data time period: 2017-01-01 to 2018-01-01

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Subjects

2D-3D registration | 3D modelling and reconstruction | Computer Vision | Computer Vision and Multimedia Computation | GOPAC | Information and Computing Sciences | calibration and pose estimation | camera pose estimation | globally-optimal | image alignment and registration | vision for robotics |

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Identifiers

DOI : 10.4225/08/5B2B4C9874FD9
Handle : 102.100.100/61740
URL : data.csiro.au/collection/csiro:25632