This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...
Many applications of computer vision requires segmenting out of an object of interest from a given image. Motivated by unlevel-sets formulation of Raviv, Kiryati and Sochen [8] and...
In this paper we present a new technique to extract layers in a video sequence. To this end, we assume that the observed scene is composed of several transparent layers, that their...
This paper is devoted to piecewise-constant segmentation of images using a curve evolution approach in a variational formulation. The problem to be solved is also called the minima...
Abstract. We match shapes, even under severe deformations, via a smooth reparametrization of their integral invariant signatures. These robust signatures and correspondences are th...
Siddharth Manay, Daniel Cremers, Anthony J. Yezzi,...
Abstract. We present an algorithm for automatically constructing a decompositional shape model from examples. Unlike current approaches to structural model acquisition, in which on...
Alex Levinshtein, Cristian Sminchisescu, Sven J. D...
Traditional stereo algorithms either explicitly use the frontal parallel plane assumption by only considering position (zero-order) disparity when computing similarity measures of ...
Abstract. We propose a new model for image decomposition which separates an image into a cartoon, consisting only of geometric objects, and an oscillatory component, consisting of ...
Abstract. We propose a model of the shape, motion and appearance of a sequence of images that captures occlusions, scene deformations, arbitrary viewpoint variations and changes in...
Jeremy D. Jackson, Anthony J. Yezzi, Stefano Soatt...
Abstract. In this paper, we present a deformable-model based solution for segmenting objects with complex texture patterns of all scales. The external image forces in traditional d...
Xiaolei Huang, Zhen Qian, Rui Huang, Dimitris N. M...