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Decoding the Grasping Intention from Electromyography during Reaching Motions

Related publications (32)

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Hand Posture Classification and Recognition using the Modified Census Transform

Sébastien Marcel, Yann Rodriguez, Agnès Just

Developing new techniques for human-computer interaction is very challenging. Vision-based techniques have the advantage of being unobtrusive and hands are a natural device that can be used for more intuitive interfaces. But in order to use hands for inter ...

IDIAP2006

Hand Posture Classification and Recognition using the Modified Census Transform

Sébastien Marcel, Yann Rodriguez, Agnès Just

2006

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

Independent Component Analysis and Support Vector Machine for Face Feature Extraction

Jean-Philippe Thiran, Gianluca Antonini, Vlad Popovici

We propose Independent Component Analysis representation and Support Vector Machine classification to extract facial features in a face detection/localization context. The goal is to find a better space where project the data in order to build ten differen ...

IEEE2003

Offline Cursive Handwriting: From Word To Text Recognition

Alessandro Vinciarelli

This thesis presents a PhD work on offline cursive handwriting recognition, the automatic transcription of cursive data when only its image is available. Two main approaches were used in the literature to solve the problem. The first one attempts to segmen ...

IDIAP2003

Mixture models for unsupervised and supervised learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

EPFL2000

Mixture Models for Unsupervised and Supervised Learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of all this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

IDIAP2000

Mixture Models for Unsupervised and Supervised Learning

École Polytechnique Fédérale de Lausanne, Computer Science Department2000

Multi-Modal Data Fusion for Person Authentication using SVM

In the context of multi-modal person authentication, a set of experts (face recognizer, speaker recognizer, etc. ) give their opinion about the identity of an individual. The opinions of the experts can be combined to form a final decision (rejecting or ac ...

1999

Multi-Modal Data Fusion for Person Authentication using SVM

IDIAP1998