Target-less registration of point clouds: A review
This is an incremental review paper for researchers in remote sensing and robotics.
This paper reviews target-less point cloud registration methods, summarizing the basic workflow and analyzing three common approach groups along with their advantages, disadvantages, and application scenarios.
Point cloud registration has been one of the basic steps of point cloud processing, which has a lot of applications in remote sensing and robotics. In this report, we summarized the basic workflow of target-less point cloud registration,namely correspondence determination and transformation estimation. Then we reviewed three commonly used groups of registration approaches, namely the feature matching based methods, the iterative closest points algorithm and the randomly hypothesis and verify based methods. Besides, we analyzed the advantage and disadvantage of these methods are introduced their common application scenarios. At last, we discussed the challenges of current point cloud registration methods and proposed several open questions for the future development of automatic registration approaches.