Multiview Range Image Registration Method

Three-dimensional objects reconstruction with 3D-scanning technology is a new technology in the field of Virtual reality, and this technology is widely used in 3D reconstruction of crime scenes, Television production, Heritage preservation and other fields. To reconstruct the three-dimensional object, one must get range images from the surface of the object. Confined by eye direction and the shape of an object, range images can not be acquired to describe the object by one scanning. To acquire a complete surface model of an object, one must scan the object from different views firstly, register range images of different views then and finally merge all range images in an unified coordinate. The key in the above process is the registration of range images, which influences the final result, the precision and automatation of 3D reconstruction.The paper introduces the process of getting 3D models using range images obtained from the laser scanning simply, introduces the theory princeple of corresponding points registration and proposed an improved registration algorithm then. ICP(Iterative Closest Point) algorithem is the most widly used registration algorithem. Nevertheless, the proper convergence of ICP is guaranteed only if one of the datasets is a subset of the other; otherwise, erroneous alignments can result. Another drawback of ICP is that it requires a good pre-alignment of the views to converge to a correct solution. In order to solve these problems, researchers have proposed some improvements based on ICP. This paper focus on analyzing ICP algorithm, as well as the advantages and disadvantages of its variants,and proposed a "coarse-to-fine" registration thinking, combined Genetic Algorithm with improved ICP to the range registration. Rough registration mainly makes use of the Genetic Algorithm's powerful global optimal search capabilities, the independence of the problem domain and the robust nature of its application. Using real-coded ,we can determine the GAs parameter settings based on experiments for range registration. After rough registration, narrowed the location between two range images, improved the stability of ICP algorithm that will be implemented. In the next registration process, the paper introduces a fast iterative pairwise registration method, which combines four acceleration techniques: fast detection of overlapped regions, more-careful selection of control points, fast surface closet point computation and compatibility test of pairing points based on the difference of modulation. Experiments show that the new algorithm is easy to implement, with quadratic precision, it is not strict for initial position and the size of overlapping part, and robust. The process of range registration is fully automated, without human intervention, and can increase the efficiency of 3D reconstruction. Finally, based on the above algorithms, implemented the 3D reconstruction module in reconstruction and intelligence analysis system of crime scenes.After summing up the research work, this paper points out some future research works.