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      Linear solution to the minimal absolute pose rolling shutter problem

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          Abstract

          This paper presents new efficient solutions to the rolling shutter camera absolute pose problem. Unlike the state-of-the-art polynomial solvers, we approach the problem using simple and fast linear solvers in an iterative scheme. We present several solutions based on fixing different sets of variables and investigate the performance of them thoroughly. We design a new alternation strategy that estimates all parameters in each iteration linearly by fixing just the non-linear terms. Our best 6-point solver, based on the new alternation technique, shows an identical or even better performance than the state-of-the-art R6P solver and is two orders of magnitude faster. In addition, a linear non-iterative solver is presented that requires a non-minimal number of 9 correspondences but provides even better results than the state-of-the-art R6P. Moreover, all proposed linear solvers provide a single solution while the state-of-the-art R6P provides up to 20 solutions which have to be pruned by expensive verification.

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          Automatic generation and detection of highly reliable fiducial markers under occlusion

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            GloptiPoly 3: moments, optimization and semidefinite programming

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              PnP Problem Revisited

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                Author and article information

                Journal
                30 December 2018
                Article
                1812.11532
                9f26654f-746b-4490-9669-90065ee12e0e

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                14th Asian Conference on Computer Vision (ACCV 2018)
                cs.CV

                Computer vision & Pattern recognition
                Computer vision & Pattern recognition

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