Determination of the Attitude of 3D Objects from a Single Perspective View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pose Determination from Line-to-Plane Correspondences: Existence Condition and Closed-Form Solutions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Review and analysis of solutions of the three point perspective pose estimation problem
International Journal of Computer Vision
Recognizing Objects Using Color-Annotated Adjacency Graphs
Shape, Contour and Grouping in Computer Vision
Complete Solution Classification for the Perspective-Three-Point Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Minimal Solution for Relative Pose with Unknown Focal Length
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
The Registration Problem Revisited: Optimal Solutions From Points, Lines and Planes
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Automatic Generator of Minimal Problem Solvers
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Accurate, Dense, and Robust Multiview Stereopsis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Monocular visual odometry and dense 3d reconstruction for on-road vehicles
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
A Theory of Minimal 3D Point to 3D Plane Registration and Its Generalization
International Journal of Computer Vision
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This paper presents a class of minimal solutions for the 3D-to-3D registration problem in which the sensor data are 3D points and the corresponding object data are 3D planes. In order to compute the 6 degrees-of-freedom transformation between the sensor and the object, we need at least six points on three or more planes. We systematically investigate and develop pose estimation algorithms for several configurations, including all minimal configurations, that arise from the distribution of points on planes. The degenerate configurations are also identified. We point out that many existing and unsolved 2D-to-3D and 3D-to-3D pose estimation algorithms involving points, lines, and planes can be transformed into the problem of registering points to planes. In addition to simulations, we also demonstrate the algorithm's effectiveness in two real-world applications: registration of a robotic arm with an object using a contact sensor, and registration of 3D point clouds that were obtained using multi-view reconstruction of planar city models.