level algorithms (perfect contours, no noise, no fragmentation, etc.). Many researchers resort to using synthetic data as their input because of this weak link. Determining groups in a given set of points or edgels can be a very expensive computational task. Not only does one need to consider all

This paper presents a novel variational framework to deal with frame partition problems in Computer Vision. This framework exploits boundary and region-based segmentation modules under a curve-based optimization objective function. The task of supervised texture segmentation is considered

We have been developing a theory for the generic representation of 2-D shape, where structural descriptions are derived from the shocks (singularities) of a curve evolution process, acting on bounding contours. We now apply the theory to the problem of shape matching. The shocks are organized

present a 3D generalization of the balloon model as a 3D deformable surface, which evolves in 3D images. It is deformed under the action of internal and external forces attracting the surface toward detected edgels by means of an attraction potential. We also show properties of energy-minimizing surfaces

algorithms can be used to find globally minimum geodesic contours (minimal surfaces in 3D) under arbitrary Riemannian metric for a given set of boundary conditions. Second, we show how to minimize metrication artifacts in existing graph-cut based methods in vision. Theoretically speaking, our work provides

This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local

, that the evolution of image intensity manifests the underlying transformation of the image due solely to the motion of objects. We then raise the question if the zerocrossing of the Laplacian operating on the image intensity is invariant too. The change of perspective view due to relative motion results

to find zeros of curvature at varying levels of detail. The result is the "generalized scale space " image of a planar curve which is invariant under rotation, uniform scaling and translation of the curve. These properties make the scale space image suitable for matching. The matching algorithm

this paper was provided to Catholic University under Grant No. 70NANB9H0923 and Grant No. 70NANB7H0716 from the National Institute of Standards and Technology

This report introduces a novel approach, called the Contour Method, to the kinematic analysis of six-degree-of-freedom serial manipulators. The inverse kinematics problem, i.e., the problem of computing all possible postures of a manipulator corresponding to a given pose---position and orientation