Pose estimation from multiple cameras based on Sylvester's equation
Computer Vision and Image Understanding
A particle filtering framework for joint video tracking and pose estimation
IEEE Transactions on Image Processing
P2Π: a minimal solution for registration of 3D points to 3D planes
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
A Theory of Minimal 3D Point to 3D Plane Registration and Its Generalization
International Journal of Computer Vision
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In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework that allows us to use both point-to-point, point-to-line and point-to-plane correspondences in the optimization algorithm. Traditional methods such as the iterative closest point algorithm may get trapped in local minima due to the non-convexity of the problem, however, our approach guarantees global optimality. The approach is based on ideas from global optimization theory, in particular, convex under-estimators in combination with branch and bound. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data.