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학술지 Fast and Reliable Minimal Relative Pose Estimation Under Planar Motion
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저자
최성록, 김종환
발행일
201801
출처
Image and Vision Computing, v.69, pp.103-112
ISSN
0262-8856
출판사
Elsevier
DOI
https://dx.doi.org/10.1016/j.imavis.2017.08.007
협약과제
17GS1300, 철도역사 안전관리 지능형 인지시스템 기술 개발 , 이재영
초록
This paper proposes fast, reliable, and minimal non-iterative relative pose solvers under planar motion constraint. Relative pose estimation is popularly utilized in many important problems such as visual odometry and SLAM, and planar motion is common for mobile robots and vehicles on floors and roads. We transform the original problem formulation of finding intersections of two ellipses into more accessible form of finding intersections of a line and unit circle. Such transformation leads to a non-iterative and closed-form solver, which enables significant speed-up compared to previous methods. The proposed algorithm is almost 9 times faster than the previous minimal solver with planar motion and around 90 times faster than the previous minimal solver with general motion. In addition, our algorithms provide reliable relative pose in degeneracy of the previous minimal planar solvers. Effectiveness of the proposed algorithms is demonstrated with two types of experiments: relative pose estimation with synthetic data and monocular visual odometry with real image sequences.
키워드
2-point algorithm, Epipolar geometry, Essential matrix, Planar motion, Relative pose estimation
KSP 제안 키워드
Epipolar geometry, Essential Matrix, Image sequence, Mobile robots, Monocular visual odometry, Motion constraint, Non-iterative, Planar motion, Problem formulation, Relative pose estimation, Speed-up