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Feature Extraction for Multi-class BCI using Canonical Variates Analysis

Publications associées (54)

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Writer Identification for Smart Meeting Room Systems

Samy Bengio, Jonas Richiardi

In this paper we present a text independent on-line writer identification system based on Gaussian Mixture Models (GMMs). This system has been developed in the context of research on Smart Meeting Rooms. The GMMs in our system are trained using two sets of ...

IDIAP2005

Kernel-based classifiers with applications to face detection

Vlad Popovici

Statistical pattern recognition occupies a central place in the general context of machine learning techniques, as it provides the theoretical insights and the practical means for solving a variety of problems ranging from character recognition to face rec ...

EPFL2004

Application of the Evidence Framework to Brain-Computer Interfaces

Touradj Ebrahimi, Ulrich Hoffmann

A brain-computer interface (BCI) is a communication system, that implements the principle of "think and make it happen without any physical effort". This means a BCI allows a user to act on his environment only by using his thoughts, without using peripher ...

IEEE2004

Direct brain-computer communication through scalp recorded EEG signals

Scalp recorded electroencephalogram signals (EEG) reflect the combined synaptic and axonal activity of groups of neurons. In addition to their clinical applications, EEG signals can be used as support for direct brain-computer communication devices (Brain- ...

EPFL2004

Multiresolution Moment Filters: Theory and Applications

Michaël Unser, Michael Sühling, Muthuvel Arigovindan

We introduce local weighted geometric moments that are computed from an image within a sliding window at multiple scales. When the window function satisfies a two-scale relation, we prove that lower order moments can be computed efficiently at dyadic scale ...

IEEE2004

Studying Phase Synchrony for Classification of Mental Tasks in Brain Machine Interfaces

José del Rocio Millán Ruiz, Silvia Chiappa

Electroencephalogram recordings during imagination of mental tasks allow for developing a new communication device for, e.g., motor disabled people. 32-channel EEG was recorded from 5 healthy subjects while performing, after instruction and in random order ...

2003

Multi-scale Feature Extraction on Point-Sampled Surfaces

Mark Pauly

We present a new technique for extracting line-type features on point-sampled geometry. Given an unstructured point cloud as input, our method first applies principal component analysis on local neighborhoods to classify points according to the likelihood ...

2003

Parametric shape processing in biomedical imaging

Mathews Jacob

In this thesis, we present a coherent and consistent approach for the estimation of shape and shape attributes from noisy images. As compared to the traditional sequential approach, our scheme is centered on a shape model which drives the feature extractio ...

EPFL2003

Multiresolution Moment Filters

Michaël Unser, Michael Sühling, Muthuvel Arigovindan

We define multi-scale moments that are estimated locally by analyzing the image through a sliding window at multiple scales. When the analysis window satisfies a two-scale relation, we prove that these moments can be computed very efficiently using a multi ...

IEEE2002

Speech Recognition Using Advanced HMM2 Features

Hervé Bourlard, Samy Bengio, Katrin Weber

HMM2 is a particular hidden Markov model where state emission probabilities of the temporal (primary) HMM are modeled through (secondary) state-dependent frequency-based HMMs [12]. As shown in [13], a secondary HMM can also be used to extract robust ASR fe ...

IDIAP2001