TY - GEN
T1 - Motion estimation of non-holonomic ground vehicles from a single feature correspondence measured over n views
AU - Huang, Kun
AU - Wang, Yifu
AU - Kneip, Laurent
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - The planar motion of ground vehicles is often non-holonomic, which enables a solution of the two-view relative pose problem from a single point feature correspondence. Man-made environments such as underground parking lots are however dominated by line features. Inspired by the planar tri-focal tensor and its ability to handle lines, we establish an n-linear constraint on the locally circular motion of non-holonomic vehicles able to handle an arbitrarily large and dense window of views. We prove that this stays a uni-variate problem under the assumption of locally constant vehicle speed, and it can transparently handle both point and vertical line correspondences. In particular, we prove that an application of Viète's formulas for extrapolating trigonometric functions of angle multiples and the Weierstrass substitution casts the problem as one that merely seeks the roots of a uni-variate polynomial. We present the complete theory of this novel solver, and test it on both simulated and real data. Our results prove that it successfully handles a variety of relevant scenarios, eventually outperforming the 1-point two-view solver.
AB - The planar motion of ground vehicles is often non-holonomic, which enables a solution of the two-view relative pose problem from a single point feature correspondence. Man-made environments such as underground parking lots are however dominated by line features. Inspired by the planar tri-focal tensor and its ability to handle lines, we establish an n-linear constraint on the locally circular motion of non-holonomic vehicles able to handle an arbitrarily large and dense window of views. We prove that this stays a uni-variate problem under the assumption of locally constant vehicle speed, and it can transparently handle both point and vertical line correspondences. In particular, we prove that an application of Viète's formulas for extrapolating trigonometric functions of angle multiples and the Weierstrass substitution casts the problem as one that merely seeks the roots of a uni-variate polynomial. We present the complete theory of this novel solver, and test it on both simulated and real data. Our results prove that it successfully handles a variety of relevant scenarios, eventually outperforming the 1-point two-view solver.
KW - 3D from Multiview and Sensors
KW - Motion and Tracking
KW - Robotics + Driving
UR - http://www.scopus.com/inward/record.url?scp=85078718559&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2019.01299
DO - 10.1109/CVPR.2019.01299
M3 - Conference contribution
AN - SCOPUS:85078718559
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SP - 12698
EP - 12707
BT - Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019
PB - IEEE Computer Society
T2 - 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019
Y2 - 16 June 2019 through 20 June 2019
ER -