Range image registration based on 2D synthetic images

Abstract

Proposed in this paper is a new procedure of range image (point cloud) registration reducing the risk of the original Iterative Closest Point (ICP) algorithm which gets stuck in a local minimum. To reduce this risk, it is essential to achieve the fine initial alignment of the given range images. The proposed procedure employs a 2D image registration method to achieve the fine initial alignment instead of a 3D feature based registration method. Although the 2D image registration method has also the risk of mismatching, we minimize the risk by increasing the number of test cases and selecting the answer that gains the most votes. To generate effective test cases, multiple 2D images are synthetized from the given range images by varying the orientation and resolution. The proposed procedure is implemented and tested for various examples, with experimental results showing that it outperforms existing methods.