TY  - CONF
AU  - Mohammad Rouhani
AU  - Angel Sappa
A2  - ECCV
PY  - 2012//
TI  - Non-Rigid Shape Registration: A Single Linear Least Squares Framework
T2  - LNCS
BT  - 12th European Conference on Computer Vision
SP  - 264
EP  - 277
VL  - 7578
PB  - Springer Berlin Heidelberg
N2  - This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided.
SN  - 0302-9743
SN  - 978-3-642-33785-7
UR  - http://dx.doi.org/10.1007/978-3-642-33786-4_20
N1  - ADAS
ID  - Mohammad Rouhani2012
ER  -