Towards 3 D lidar point cloud registration improvement using optimal neighborhood knowledge

@inproceedings{Gressin2013Towards3D,
  title={Towards 3 D lidar point cloud registration improvement using optimal neighborhood knowledge},
  author={Adrien Gressin and Cl{\'e}ment Mallet and J{\'e}r{\^o}me Demantk{\'e} and N. David},
  year={2013}
}
Automatic 3D point cloud registration is a main issue in computer vision and remote sensing. One of the most commonly adopted solution is the well-known Iterative Closest Point (ICP) algorithm. This standard approach performs a fine registration of two overlapping point clouds by iteratively estimating the transformation parameters, assuming good a priori alignment is provided. A large body of literature has proposed many variations in order to improve each step of the process (namely selecting… CONTINUE READING
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