We propose the first fast and certifiable algorithm for the registration of two sets of three-
dimensional (3-D) points in the presence of large amounts of outlier correspondences. A …

With the development of 3D matching technology, correspondence-based point cloud
registration gains more attention. Unfortunately, 3D keypoint techniques inevitably produce …

Point cloud registration is a key problem for computer vision applied to robotics, medical
imaging, and other applications. This problem involves finding a rigid transformation from …

Methods tackling multi-object tracking need to estimate the number of targets in the sensing
area as well as to estimate their continuous state. While the majority of existing methods …

We study the problem of extracting accurate correspondences for point cloud registration.
Recent keypoint-free methods bypass the detection of repeatable keypoints which is difficult …

We present DeepVCP-a novel end-to-end learning-based 3D point cloud registration
framework that achieves comparable registration accuracy to prior state-of-the-art geometric …

Outlier removal is a critical part of feature-based point cloud registration. In this article, we
revisit the model generation and selection of the classic RANSAC approach for fast and …

Point cloud registration, which effectively coincides the source and target point clouds, is
generally implemented by geometric metrics or feature metrics. In terms of resistance to …

In this paper, we present a second order spatial compatibility (SC^ 2) measure based
method for efficient and robust point cloud registration (PCR), called SC^ 2-PCR. Firstly, we …

An ideal point cloud registration framework should have superior accuracy, acceptable
efficiency, and strong generalizability. However, this is highly challenging since existing …