In this work we propose a method for estimating disparity maps from very few
measurements. Based on the theory of Compressive Sensing, our algorithm accurately …

This paper describes a new variational method for estimating disparity from stereo images.
The stereo matching problem is formulated as a convex programming problem in which an …

Estimating the disparity field between two stereo images is a common task in computer
vision, eg, to determine a dense depth map. Variational methods currently are among the …

A new divide-and-conquer technique for disparity estimation is proposed in this paper. This
technique performs feature matching following the high confidence first principle, starting …

This paper presents the design, implementation and evaluation of new parallelization
schemes for performing dense disparity estimation based on non-parametric rank transform …

We present an energy based approach to estimate a dense disparity map from a set of two
weakly calibrated stereoscopic images while preserving its discontinuities resulting from …

In this paper, we propose a hierarchical disparity estimation algorithm with energy-based
regularization. Initial disparity vectors are obtained from downsampled stereo images using …

We present a method for computing dense visual correspondence based on general
assumptions about scene geometry. Our algorithm does not rely on correlation, and uses a …

In this paper we propose extensions to the match propagation algorithm which is a
technique for computing quasi-dense point correspondences between two views. The …

This work presents two techniques for computing dense disparity maps from two or more
images. These methods are exploited in an application of augmented reality in order to add …