Rami Ben-Ari

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This paper addresses the problem of correspondence establishment in binocular stereo vision. We suggest a novel variational approach that considers both the discontinuities and occlusions. It deals with color images as well as gray levels. The proposed method divides the image domain into the visible and occluded regions where each region is handled(More)
This paper addresses the problem of correspondence establishment in binocular stereo vision. We suggest a novel spatially continuous approach for stereo matching based on the variational framework. The proposed method suggests a unique regularization term based on Mumford-Shah functional for discontinuity preserving, combined with a new energy functional(More)
We evaluate the dense optical flow between two frames via variational approach. In this paper, a new framework for deriving the regularization term is introduced giving a geometric insight into the action of a smoothing term. The framework is based on the Beltrami paradigm in image denoising. It includes a general formulation that unifies several previous(More)
OBJECTIVE The aim was to study the effects of the collagen mesh that interconnects the myocardial fibres on left ventricular mechanics and intramyocardial pressure. METHODS An earlier model which integrates a symmetrical left ventricular geometry and transmural muscle fibre structure with muscle fibre mechanics was expanded to include radial stiffness(More)
The problem of dense optical flow computation is addressed from a variational viewpoint. A new geometric framework is introduced. It unifies previous art and yields new efficient methods. Along with the framework a new alignment criterion suggests itself. It is shown that the alignment between the gradients of the optical flow components and between the(More)
With emerging of next generation of digital cameras offering a 3D reconstruction of a viewed scene, Depth from Defocus (DFD) presents an attractive option. In this approach the depth profile of the scene is recovered from two views captured in different focus setting. The DFD is well known as a computationally-intensive method due to the shift-variant(More)
Every stereovision application must cope with the correspondence problem. The space of the matching variables, often consisting of spatial coordinates, intensity and disparity, is commonly referred as the data term (space). Since the data is often noisy a-priori, preference is required to result a smooth disparity (or piecewise smooth). To this end, each(More)