You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A review of recent range image registration methods with accuracy evaluation 
Chapter Title:  Ransac-based darces 
1. Abstract of Cited Paper (BIB001):  In this paper, we propose a new method, the RANSAC-based DARCES method (data-aligned rigidity-constrained exhaustive search based on random sample consensus), which can solve the partially overlapping 3D registration problem without any initial estimation. For the noiseless case, the basic algorithm of our method can guarantee that the solution it finds is the true one, and its time complexity can be shown to be relatively low. An extra characteristic is that our method can be used even for the case that there are no local features in the 3D data sets.

Literature Review:
This method is based on finding the best three point-correspondences between two range images to obtain an estimation of the Euclidean motion. Three points are the minimum required to compute the motion between both surfaces if no other information is used BIB001 . As will be commented in Section 3.8, Feldmar used only a single point but also considered the normal vector and the principal curvature to obtain enough information to compute the rigid motion  . Three points (primary, secondary and auxiliary) in the first view are characterized by the three distances between them (d ps , d pa and d sa ). Each point in the second view is hypothesized to be the correspondence of the primary point (p 0 ). Next, the secondary point is searched for among the points located at a distance d ps from p 0 . If there are not any points in that position, another primary point is tested. Otherwise, a third point in the second view that satisfies the distances defined in the triplet is searched. Once a triplet is identified, the rigid transformation between both points can be determined. This search is repeated exhaustively for every satisfied triplet between both views and a set of potential Euclidean motions is obtained. The correct transformation is the one that obtains the largest number of corresponding points between both views. A modification of this method focused on decreasing the computing time related to the search of correspondences was proposed BIB002 . The results obtained were very good because of its robustness even in the presence of outliers. However, it can only be used when the number of points in each view is relatively small. Theoretically it is a good method. However, the precision depends on the resolution of the surface and the time increases considerably with the number of points, so that it can only be used in applications where time is not critical.