Spatiotemporal stereo is concerned with recovery of the 3D structure of a
dynamically changing scene from a sequence of stereo images. This paper
aims at computing temporally coh...
Object recognition, robotic vision, occluding noise removal or photograph design require the ability to perform disocclusion. We call disocclusion the recovery of hidden parts of ...
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...
In wide-coverage lexicalized grammars many of the elementary structures have substructures in common. This means that in conventional parsing algorithms some of the computation as...
This article extends the concept of compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, whic...
Holger Rauhut, Karin Schnass, Pierre Vandergheynst