In this paper, we propose an image segmentation technique based on augmenting the conformal (or geodesic) active contour framework with directional information. In the isotropic ca...
John Melonakos, Eric Pichon, Sigurd Angenent, Alle...
In this paper, the duality in differential form is developed between a 3D primal surface and its dual manifold formed by the surface's tangent planes, i.e., each tangent plan...
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
We propose a geometric approach to 3D motion segmentation from point correspondences in three perspective views. We demonstrate that after applying a polynomial embedding to the po...
Although it has been studied for years by the computer vision and machine learning communities, image annotation is still far from practical. In this paper, we propose a novel atte...
Xin-Jing Wang, Lei Zhang 0001, Xirong Li, Wei-Ying...
We present a novel algorithm for detection of certain types of unusual events. The algorithm is based on multiple local monitors which collect low-level statistics. Each local moni...
Amit Adam, Ehud Rivlin, Ilan Shimshoni, David Rein...
Image denoising algorithms often assume an additive white Gaussian noise (AWGN) process that is independent of the actual RGB values. Such approaches cannot effectively remove colo...
Ce Liu, Richard Szeliski, Sing Bing Kang, C. Lawre...
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
This paper develops a theory of frequency domain invariants in computer vision. We derive novel identities using spherical harmonics, which are the angular frequency domain analog ...