Concept

Fléau de la dimension

Publications associées (331)

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

Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime

Martin Vetterli, Olivier Roy

Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated with the signal of interest. The acquired data is then wirelessly transmitted ...

Institute of Electrical and Electronics Engineers2008

LSH At Large - Distributed KNN Search in High Dimensions

Karl Aberer, Sebastian Michel, Parisa Haghani

We consider K-Nearest Neighbor search for high dimensional data in large-scale structured Peer-to-Peer networks. We present an efficient mapping scheme based on p-stable Locality Sensitive Hashing to assign hash buckets to peers in a Chord-style overlay ne ...

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

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

Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations: Application to transport and continuum mechanics

Gianluigi Rozza

In this paper we consider (hierarchical, Lagrange) reduced basis approximation and a posteriori error estimation for linear functional outputs of affinely parametrized elliptic coercive partial differential equations. The essential ingredients are (primal- ...

2008

Fast human detection from videos using covariance features

Jean-Marc Odobez

In this paper, we present a fast method to detect humans from videos captured in surveillance applications. It is based on a cascade of LogitBoost classifiers relying on features mapped from the Riemanian manifold of region covariance matrices computed fro ...

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

On finding approximate nearest neighbours in a set of compressible signals

Pierre Vandergheynst, Philippe Jost

Numerous applications demand that we manipulate large sets of very high-dimensional signals. A simple yet common example is the problem of finding those signals in a database that are closest to a query. In this paper, we tackle this problem by restricting ...

2008

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