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Publications associées (207)

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Daniel Gatica-Perez, Jean-Marc Odobez, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas

We present a novel approach for contextual segmentation of complex visual scenes, based on the use of bags of local invariant features (visterms) and probabilistic aspect models. Our approach uses context in two ways: (1) by using the fact that specific le ...

IDIAP2005

Temperature dependence of the dielectric tunability of pyrochlore bismuth zinc niobate thin films

Alexander Tagantsev

The change in permittivity of bismuth zinc niobate (BZN) films with the cubic pyrochlore structure under an applied electric field was measured as a function of temperature. Dielectric measurements were performed using parallel-plate capacitor structures w ...

2005

Power Control for Target Tracking in Sensor Networks

Razvan Cristescu, Jean-Paul Wagner

We consider the problem of a sensor network tracking a moving target that exhibits a Markov model of mobility. The sensor nodes have adjustable power levels and the precision of the measurement of the target location depends on both the relative distance f ...

2005

A Discriminative Decoder for the Recognition of Phoneme Sequences

Samy Bengio, David Grangier

In this report, we propose a discriminative decoder for phoneme recognition, i.e. the identification of the uttered phoneme sequence from a speech recording. This task is solved as a 3 step process: a phoneme classifier first classifies each accoustic fram ...

IDIAP2005

Percolation in the signal to interference ratio graph

Patrick Thiran, Nicolas Macris, Olivier Dousse

Continuum percolation models in which pairs of points of a two-dimensional Poisson point process are connected if they are within some range to each other have been extensively studied. This paper considers a variation in which a connection between two poi ...

2005

Sequence Classification with Input-Output Hidden Markov Models

Samy Bengio, Silvia Chiappa

We present a training and testing method for Input-Output Hidden Markov Model that is particularly suited for classification of sequences in which class information accumulates over time. We discuss two such cases: the discrimination of mental tasks from s ...

IDIAP2004

An Auxiliary Variational Method

Variational methods have proved popular and effective for inference and learning in intractable graphical models. An attractive feature of the approaches based on the Kullback-Leibler divergence is a rigorous lower bound on the normalization constants in u ...

IDIAP2004

Validation of Tissue Modelization and Classification Techniques in T1-weighted MR Brain Images

Jean-Philippe Thiran, Meritxell Bach Cuadra, Leila Cammoun, Olivier Cuisenaire, Torsten Butz

We propose a deep study on tissue modelization and classification techniques on T1-weighted MR images. Six approaches have been taken into account to perform this validation study. We consider first the Finite Gaussian Mixture model (A-FGMM) and a Bayes cl ...

2004

HMM and IOHMM for the Recognition of Mono- and Bi-Manual 3D Hand Gestures

Sébastien Marcel, Agnès Just

In this paper, we address the problem of the recognition of isolated complex mono- and bi-manual hand gestures. In the proposed system, hand gestures are represented by the 3D trajectories of blobs obtained by tracking colored body parts. In this paper, we ...

IDIAP2004

Topology Learning and Place Recognition using Bayesian Programming for Mobile Robot Navigation

Roland Siegwart, Adriana Tapus, Guy Ramel

This paper proposes an approach allowing topology learning and recognition in indoor environments by using a probabilistic approach called Bayesian Programming. The main goal of this approach is to cope with the uncertainty, imprecision and incompleteness ...

2004

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