학술논문

Structured Down-Sampling and Registration Method for 3D Point Cloud of Indoor Scene
Document Type
Conference
Source
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on. :1596-1601 Oct, 2019
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Three-dimensional displays
Principal component analysis
Eigenvalues and eigenfunctions
Sensors
Feature extraction
Iterative closest point algorithm
Sampling methods
Language
ISSN
2577-1655
Abstract
In this paper, noted by the regular geometric structure of indoor scene, a biased down-sampling scheme is designed to automatically adjust the local sampling rate according to the local density and distribution. Our down-sampling results can effectively remain the main structure while greatly reduce the data number for the following work. Moreover, an improved Iterative Closest Point (ICP) algorithm for point clouds registration is proposed with the prior of structure information. Sampled structured data is weighted to give their contributions for registration. This leads the parameter estimation to naturally focus on aligning the structures of indoor scenes. The experimental results demonstrate the effectiveness of the proposed method on improving the registration accuracy with the same level of down-sampling data.