TY  - CONF
AU  - Mohammad Rouhani
AU  - Angel Sappa
A2  - ICCV
PY  - 2011//
TI  - Correspondence Free Registration through a Point-to-Model Distance Minimization
BT  - 13th IEEE International Conference on Computer Vision
SP  - 2150
EP  - 2157
N2  - This paper presents a novel formulation, which derives in a smooth minimization problem, to tackle the rigid registration between a given point set and a model set. Unlike most of the existing works, which are based on minimizing a point-wise correspondence term, we propose to describe the model set by means of an implicit representation. It allows a new definition of the registration error, which works beyond the point level representation. Moreover, it could be used in a gradient-based optimization framework. The proposed approach consists of two stages. Firstly, a novel formulation is proposed that relates the registration parameters with the distance between the model and data set. Secondly, the registration parameters are obtained by means of the Levengberg-Marquardt algorithm. Experimental results and comparisons with state of the art show the validity of the proposed framework.
SN  - 1550-5499
SN  - 978-1-4577-1101-5
UR  - http://dx.doi.org/10.1109/ICCV.2011.6126491
N1  - ADAS
ID  - Mohammad Rouhani2011
ER  -