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These last years, artificial neural networks (ANN) have known a renewed interest since efficient training procedures have emerged to learn the so called deep neural networks (DNN), i.e. ANN with at least two hidden layers. In the same time, the computational auditory scene recognition (CASR) problem which consists in estimating the environment around a(More)
In this paper, we present the main results of the BioSecure Signature Evaluation Campaign (BSEC'2009). The objective of BSEC'2009 was to evaluate different online signature algorithms on two tasks: the first one aims at studying the influence of acquisition conditions (digitizing tablet or PDA) on systems' performance; the second one aims at studying the(More)
This paper describes the objectives, the tasks proposed to the participants and the associated protocols in terms of database and assessment tools of two present competitions on fingerprints and on-line signatures, the results of which will be ready for presentation at the next ICB conference. The particularity of the fingerprint competition is to be an(More)
In this document, we present the participants and report the experimental results on the three Evaluations conducted in BSEC'2009. We also report the results obtained with BioSecure Reference System We only give a limited analysis of results, and in particular we do not compare systems between them. Indeed, we aim at publishing results in a Journal(More)
In this article, we present a new tool for sparse coding : Multivariate DLA which empirically learns the characteristic patterns associated to a multivariate signals set. Once learned, Multivariate OMP approximates sparsely any signal of this considered set. These methods are specified to the 2D rotation-invariant case. Shift and rotation-invariant cases(More)
The BioSecure Network of Excellence has collected a large multi- biometric publicly available database and organized the BioSecure Multimodal Evaluation Campaigns (BMEC) in 20072. This paper reports on the Talking Faces campaign. Open source reference systems were made available to participants and four laboratories submitted executable code to the(More)
Classical dictionary learning algorithms (DLA) allow unicomponent signals to be processed. Due to our interest in two-dimensional (2D) motion signals, we wanted to mix the two components to provide rotation invariance. So, multicomponent frameworks are examined here. In contrast to the well-known multichannel framework, a multivariate framework is first(More)
On one hand, sparse coding, which is widely used in signal processing, consists of representing signals as linear combinations of few elementary patterns selected from a dedicated dictionary. The output is a sparse vector containing few coding coefficients and is called sparse code. On the other hand, Multilayer Perceptron (MLP) is a neural network(More)
This paper focuses on the common evaluation framework which was developed by the BioSecure Network of Excellence during the European FP6 project BioSecure (Biometrics for Secure authentication). This framework, which is composed of open-source reference systems, publicly available databases, assessment protocols and benchmarking results, introduces a new(More)