D. Metaxas et al., MULTILEVEL SHAPE REPRESENTATION USING GLOBAL DEFORMATIONS AND LOCALLYADAPTIVE FINITE-ELEMENTS, International journal of computer vision, 25(1), 1997, pp. 49-61
Citations number
29
Categorie Soggetti
Computer Sciences, Special Topics","Computer Science Artificial Intelligence
We present a model-based method for the multi-level shape, pose estima
tion and abstraction of an object's surface from range data. The surfa
ce shape is estimated based on the parameters of a superquadric that i
s subjected to global deformations (tapering and bending) and a varyin
g number of levels of local deformations. Local deformations are imple
mented using locally adaptive finite elements whose shape functions ar
e piecewise cubic functions with C-1 continuity. The surface pose is e
stimated based on the model's translational and rotational degrees of
freedom. The algorithm first does a coarse fit, solving for a first ap
proximation to the translation, rotation and global deformation parame
ters and then does several passes of mesh refinement, by locally subdi
viding triangles based on the distance between the given datapoints an
d the model. The adaptive finite element algorithm ensures that during
subdivision the desirable finite element mesh generation properties o
f conformity, non-degeneracy and smoothness are maintained. Each pass
of the algorithm uses physics-based modeling techniques to iteratively
adjust the global and local parameters of the model in response to fo
rces that are computed from approximation errors between the model and
the data. We present results demonstrating the multi-level shape repr
esentation for both sparse and dense range data.