Publications related to Dimensionality Reduction with Adaptive Approximation

Semantic coding by supervised dimensionality reduction

This paper addresses the problem of representing multimedia information under a compressed form that permits efficient classification. The semantic coding problem starts from a subspace method where dimensionality reduction is formulated as a matrix factor ...

2008

Tracking Articulated Bodies using Generalized Expectation Maximization

Pascal Fua, Andrea Fossati

A generalized expectation maximization (GEM) algorithm is used to retrieve the pose of a person from a monocular video sequence shot with a moving camera. After embedding the set of possible poses in a low dimensional space using principal component analys ...

2008

3D Face Recognition using Sparse Spherical Representations

Pascal Frossard, Effrosyni Kokiopoulou, Ivana Tosic, Roser Sala Llonch

This paper addresses the problem of 3D face recognition using spherical sparse representations. We first propose a fully automated registration process that permits to align the 3D face point clouds. These point clouds are then represented as signals on th ...

2008

Some Recovery Conditions for Basis Learning by L1-Minimization

Rémi Gribonval, Karin Schnass

Many recent works have shown that if a given signal admits a sufficiently sparse representation in a given dictionary, then this representation is recovered by several standard optimization algorithms, in particular the convex

\ell^1

minimization approac ...

2008

Dictionary Learning Based Dimensionality Reduction for Classification

Pierre Vandergheynst, Karin Schnass

In this article we present a signal model for classification based on a low dimensional dictionary embedded into the high dimensional signal space. We develop an alternate projection algorithm to find the embedding and the dictionary and finally test the c ...

2008

Compressed sensing and redundant dictionaries

Pierre Vandergheynst, Karin Schnass

This article extends the concept of it compressed sensing to signals that are not sparse in an orthonormal basis but rather in a redundant dictionary. It is shown that a matrix, which is a composition of a random matrix of certain type and a deterministic ...

2008

On the estimation of geodesic paths on sampled manifolds after random projections

Pierre Vandergheynst, Matteo Sorci

In this paper, we focus on the use of random projections as a dimensionality reduction tool for sampled manifolds in high-dimensional Euclidean spaces. We show that geodesic paths approximations from nearest neighbors Euclidean distances are well-preserved ...

2008

Sparse image approximation with application to flexible image coding

Natural images are often modeled through piecewise-smooth regions. Region edges, which correspond to the contours of the objects, become, in this model, the main information of the signal. Contours have the property of being smooth functions along the dire ...

EPFL2005

Toward sparse and geometry adapted video approximations

Oscar Divorra Escoda

Video signals are sequences of natural images, where images are often modeled as piecewise-smooth signals. Hence, video can be seen as a 3D piecewise-smooth signal made of piecewise-smooth regions that move through time. Based on the piecewise-smooth model ...

EPFL2005

Analysis of Multimodal Signals Using Redundant Representations [Winner of IBM Student Paper Award]

Pierre Vandergheynst, Gianluca Monaci, Oscar Divorra Escoda

In this work we explore the potentialities of a framework for the representation of audio-visual signals using decompositions on overcomplete dictionaries. Redundant decompositions may describe audio-visual sequences in a concise fashion, preserving good r ...

2005

Dimensionality Reduction with Adaptive Approximation

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Semantic coding by supervised dimensionality reduction

Tracking Articulated Bodies using Generalized Expectation Maximization

3D Face Recognition using Sparse Spherical Representations

Some Recovery Conditions for Basis Learning by L1-Minimization

Dictionary Learning Based Dimensionality Reduction for Classification

Compressed sensing and redundant dictionaries

On the estimation of geodesic paths on sampled manifolds after random projections

Sparse image approximation with application to flexible image coding

Toward sparse and geometry adapted video approximations

Analysis of Multimodal Signals Using Redundant Representations [Winner of IBM Student Paper Award]

Semantic coding by supervised dimensionality reduction

Tracking Articulated Bodies using Generalized Expectation Maximization

3D Face Recognition using Sparse Spherical Representations

Compressed sensing and redundant dictionaries

Some Recovery Conditions for Basis Learning by L1-Minimization

Dictionary Learning Based Dimensionality Reduction for Classification

Sparse image approximation with application to flexible image coding

Toward sparse and geometry adapted video approximations

On the estimation of geodesic paths on sampled manifolds after random projections

Analysis of Multimodal Signals Using Redundant Representations [Winner of IBM Student Paper Award]