Regularized point-to-point and point-to-plane functionals in the point clouds registration problem
- Resource Type
- Conference
- Authors
- Makovetskii, Artyom; Voronin, Sergei; Kober, Vitaly; Voronin, Alexei
- Source
- 2021 International Conference on Information Technology and Nanotechnology (ITNT) Information Technology and Nanotechnology (ITNT), 2021 International Conference on. :1-6 Sep, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Signal Processing and Analysis
Point cloud compression
Three-dimensional displays
Closed-form solutions
Iterative closest point algorithm
Computer simulation
Approximation algorithms
Information technology
variational functional
exact solution
closed-form solution
orthogonal transformation
iterative closest point algorithm (ICP)
- Language
Point cloud alignment looks for either rigid or non-rigid geometric transformation in 3D space that optimizes the overlap of two point clouds. The Iterative Closest Point (ICP) algorithm is the most known algorithm for combining point clouds used only geometrical features. An important component of the ICP algorithm is the variational subproblem of the algorithm. Point-to-point and point-to-plane functionals are the most commonly used in the variational ICP subproblem. This paper deals with regularized versions of the variational problems. The proposed approach significantly increases the performance of the conventional ICP algorithm.