Title: A Branch-and-Bound Algorithm for Checkerboard Extraction in Camera-Laser Calibration,
Abstract: We address the problem of camera-to-laser-scanner calibration using a
checkerboard and multiple image-laser scan pairs. Distinguishing which laser
points measure the checkerboard and which lie on the background is essential to
any such system. We formulate the checkerboard extraction as a combinatorial
optimization problem with a clear cut objective function. We propose a
branch-and-bound technique that deterministically and globally optimizes the
objective. Unlike what is available in the literature, the proposed method is
not heuristic and does not require assumptions such as constraints on the
background or relying on discontinuity of the range measurements to partition
the data into line segments. The proposed approach is generic and can be
applied to both 3D or 2D laser scanners as well as the cases where multiple
checkerboards are present. We demonstrate the effectiveness of the proposed
approach by providing numerical simulations as well as experimental results.