Fully Automatic Registration of 3D Point Clouds


We propose a novel technique for the registration of 3D point clouds which makes very few assumptions: we avoid any manual rough alignment or the use of landmarks, displacement can be arbitrarily large, and the two point sets can have very little overlap. Crude alignment is achieved by estimation of the 3D-rotation from two Extended Gaussian Images even… (More)
DOI: 10.1109/CVPR.2006.122


8 Figures and Tables


Citations per Year

231 Citations

Semantic Scholar estimates that this publication has 231 citations based on the available data.

See our FAQ for additional information.

Slides referencing similar topics