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 ob...
In this paper we consider a quantized discrete-time linear quadratic regulator (DLQR) problem, namely a DLQR problem where the input u may only take values in a given finite set ...
In this paper, we present a new segment-based stereo matching algorithm using graph cuts. In our approach, the reference image is divided into non-overlapping homogeneous segments...
This paper presents a probabilistic framework for computing correspondences and fundamental matrix in the structure from motion problem. Inspired by Moisan and Stival [1], we sugg...
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...