PR-Alignment: Multidimensional Adaptive Registration Algorithm Based on Practical Application Scenarios

In the present day, 3D point clouds are considered to be an important form of representing world. computer vision, mobile robotics, and graphics, cloud registration is a basic task, it widely used in reconstruction, reverse engineering, among other applications. However, mainstream method subject problems long time as well poor modeling effect, these two factors cannot balanced. To address this issue, we propose adaptive mechanism based on multi-dimensional analysis practical application scenarios. Through use laser RGB images, able obtain geometric photometric information, thus improving data dimension. By adding target scene classification information RANSAC algorithm, combined with matching matching, complete estimation transformation matrix. We demonstrate via extensive experiments that our achieves state-of-the-art performance terms accuracy compared algorithms, striking balance between expected cost.