1 research outputs found
Can generalised relative pose estimation solve sparse 3D registration?
Popular 3D scan registration projects, such as Stanford digital Michelangelo
or KinectFusion, exploit the high-resolution sensor data for scan alignment. It
is particularly challenging to solve the registration of sparse 3D scans in the
absence of RGB components. In this case, we can not establish point
correspondences since the same 3D point cannot be captured in two successive
scans. In contrast to correspondence based methods, we take a different
viewpoint and formulate the sparse 3D registration problem based on the
constraints from the intersection of line segments from adjacent scans. We
obtain the line segments by modeling every horizontal and vertical scan-line as
piece-wise linear segments. We propose a new alternating projection algorithm
for solving the scan alignment problem using line intersection constraints. We
develop two new minimal solvers for scan alignment in the presence of plane
correspondences: 1) 3 line intersections and 1 plane correspondence, and 2) 1
line intersection and 2 plane correspondences. We outperform other competing
methods on Kinect and LiDAR datasets