Robust and efficient map-to-image registration with line segments

Abstract. This work investigates map-to-image registration for planar scenes in the context of robust parameter estimation. Registration is posed as the problem of estimating a projective transformation which optimally aligns transformed model line segments from a map with data line segments extracted from an image. Matching and parameter estimation is solved simultaneously by optimizing an objective function which is based on M-estimators, and depends on overlap and the weighted orthogonal distance between transformed model segments and data segments. An extensive series of registration experiments was conducted to test the performance of the proposed parameter estimation algorithm. More than 200 000 registration experiments were run with different objective functions for 12 aerial images and randomly corrupted maps distorted by randomly selected projective transformations.