We present an approach to computing a curve atlas based on deriving a correspondence between two curves. This correspondence is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature. The optimal correspondence is found by an efficient dynamicprogramming method. This is then used to compute an average for a set of curves and applied to computing the averages of bone shapes and corpus callosum as examples, towards constructing a computational atlas. The proposed notion of alignment also leads to a registration method, which is illustrated with several examples
We present a method for matching curves which accommodates large and small deformation. The method p...
Natural surfaces are usually associated with feature graphs, such as the cortical surface with anato...
The proposed thesis focuses on providing definitions, closed-form expressions and algorithmic soluti...
We present a 2D shape recognition and classification method based on matching shape outlines. The co...
A problem, often encountered in functional data analysis, is misalignment of the data. Many methods ...
There are many algorithms for computing curve skeletons. Most of them have their own notion of what ...
MICA enables the automatic synchronization of discrete data curves. To this end, characteristic poin...
One of the key challenges in deformable shape modeling is the problem of estimating a meaningful ave...
International audienceComputing, visualizing and interpreting statistics on shapes like curves or su...
Curve matching is essential to many design and manufacturing applications as well as in image proces...
3D deformable registration, Two-level method, Statistical atlas Abstract: We propose a two-level met...
Congealing is a flexible nonparametric data-driven framework for the joint alignment of data. It has...
For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape m...
For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape m...
This paper deals with analysis, research and implementation of various methods of curve representati...
We present a method for matching curves which accommodates large and small deformation. The method p...
Natural surfaces are usually associated with feature graphs, such as the cortical surface with anato...
The proposed thesis focuses on providing definitions, closed-form expressions and algorithmic soluti...
We present a 2D shape recognition and classification method based on matching shape outlines. The co...
A problem, often encountered in functional data analysis, is misalignment of the data. Many methods ...
There are many algorithms for computing curve skeletons. Most of them have their own notion of what ...
MICA enables the automatic synchronization of discrete data curves. To this end, characteristic poin...
One of the key challenges in deformable shape modeling is the problem of estimating a meaningful ave...
International audienceComputing, visualizing and interpreting statistics on shapes like curves or su...
Curve matching is essential to many design and manufacturing applications as well as in image proces...
3D deformable registration, Two-level method, Statistical atlas Abstract: We propose a two-level met...
Congealing is a flexible nonparametric data-driven framework for the joint alignment of data. It has...
For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape m...
For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape m...
This paper deals with analysis, research and implementation of various methods of curve representati...
We present a method for matching curves which accommodates large and small deformation. The method p...
Natural surfaces are usually associated with feature graphs, such as the cortical surface with anato...
The proposed thesis focuses on providing definitions, closed-form expressions and algorithmic soluti...