Efficient Solvers for Minimal Problems by Syzygy-based Reduction
Larsson, Viktor; Åström, Karl; Oskarsson, Magnus (2017-07). Efficient Solvers for Minimal Problems by Syzygy-based Reduction IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2383 - 2392. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. Honolulu, United States: IEEE - Institute of Electrical and Electronics Engineers Inc.
Conference Proceeding/Paper
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Published
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English
Authors:
Larsson, Viktor
;
Åström, Karl
;
Oskarsson, Magnus
Department:
Mathematics (Faculty of Engineering)
ELLIIT: the Linköping-Lund initiative on IT and mobile communication
Project:
Semantic Mapping and Visual Navigation for Smart Robots
Abstract:
In this paper we study the problem of automatically generating
polynomial solvers for minimal problems. The main
contribution is a new method for finding small elimination
templates by making use of the syzygies (i.e. the polynomial
relations) that exist between the original equations. Using
these syzygies we can essentially parameterize the set
of possible elimination templates.
We evaluate our method on a wide variety of problems
from geometric computer vision and show improvement
compared to both handcrafted and automatically generated
solvers. Furthermore we apply our method on two previously
unsolved relative orientation problems.
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