Idiap Research Institute

Displaying 1-6 of 6 results

  • White Papers // Feb 2010

    Feature Distribution Modelling Techniques for 3D Face Verification

    This paper shows that Hidden Markov Models (HMMs) can be effectively applied to 3D face data. The examined HMM techniques are shown to be superior to a previously examined Gaussian Mixture Model (GMM) technique. Experiments conducted on the Face Recognition Grand Challenge database show that the Equal Error Rate can...

    Provided By Idiap Research Institute

  • White Papers // Jun 2009

    Hill-Climbing Attack to an Eigenface-Based Face Verification System

    The authors use a general hill-climbing attack algorithm based on Bayesian adaption to test the vulnerability of an Eigenface-based approach for face recognition against indirect attacks. The attacking technique uses the scores provided by the matcher to adapt a global distribution, computed from a development set of users, to the...

    Provided By Idiap Research Institute

  • White Papers // Jun 2007

    Biometric Person Authentication IS A Multiple Classifier Problem

    Several papers have already shown the interest of using multiple classifiers in order to enhance the performance of biometric person authentication systems. In this paper, the authors would like to argue that the core task of biometric person authentication is actually a multiple classifier problem as such: indeed, in order...

    Provided By Idiap Research Institute

  • White Papers // May 2007

    On the Recent Use of Local Binary Patterns for Face Authentication

    In this paper, the authors present a survey on the recent use of Local Binary Patterns (LBPs) for face recognition. LBP is becoming a popular technique for face representation. It is a non-parametric kernel which summarizes the local spacial structure of an image and it is invariant to monotonic gray-scale...

    Provided By Idiap Research Institute

  • White Papers // May 2007

    Face Authentication with Salient Local Features and Static Bayesian Network

    In this paper, the problem of face authentication using salient facial features together with statistical generative models is addressed. Actually, classical generative models, and Gaussian Mixture Models in particular make strong assumptions on the way observations derived from face images are generated. Indeed, systems proposed so far consider that local...

    Provided By Idiap Research Institute

  • White Papers // Jul 2006

    Performance Generalization in Biometric Authentication Using Joint User-Specific and Sample Bootstraps

    Biometric authentication performance is often depicted by a DET curve. The authors show that this curve is dependent on the choice of samples available, the demographic composition and the number of users specific to a database. They propose a two-step bootstrap procedure to take into account of the three mentioned...

    Provided By Idiap Research Institute

  • White Papers // Feb 2010

    Feature Distribution Modelling Techniques for 3D Face Verification

    This paper shows that Hidden Markov Models (HMMs) can be effectively applied to 3D face data. The examined HMM techniques are shown to be superior to a previously examined Gaussian Mixture Model (GMM) technique. Experiments conducted on the Face Recognition Grand Challenge database show that the Equal Error Rate can...

    Provided By Idiap Research Institute

  • White Papers // Jun 2009

    Hill-Climbing Attack to an Eigenface-Based Face Verification System

    The authors use a general hill-climbing attack algorithm based on Bayesian adaption to test the vulnerability of an Eigenface-based approach for face recognition against indirect attacks. The attacking technique uses the scores provided by the matcher to adapt a global distribution, computed from a development set of users, to the...

    Provided By Idiap Research Institute

  • White Papers // May 2007

    Face Authentication with Salient Local Features and Static Bayesian Network

    In this paper, the problem of face authentication using salient facial features together with statistical generative models is addressed. Actually, classical generative models, and Gaussian Mixture Models in particular make strong assumptions on the way observations derived from face images are generated. Indeed, systems proposed so far consider that local...

    Provided By Idiap Research Institute

  • White Papers // May 2007

    On the Recent Use of Local Binary Patterns for Face Authentication

    In this paper, the authors present a survey on the recent use of Local Binary Patterns (LBPs) for face recognition. LBP is becoming a popular technique for face representation. It is a non-parametric kernel which summarizes the local spacial structure of an image and it is invariant to monotonic gray-scale...

    Provided By Idiap Research Institute

  • White Papers // Jul 2006

    Performance Generalization in Biometric Authentication Using Joint User-Specific and Sample Bootstraps

    Biometric authentication performance is often depicted by a DET curve. The authors show that this curve is dependent on the choice of samples available, the demographic composition and the number of users specific to a database. They propose a two-step bootstrap procedure to take into account of the three mentioned...

    Provided By Idiap Research Institute

  • White Papers // Jun 2007

    Biometric Person Authentication IS A Multiple Classifier Problem

    Several papers have already shown the interest of using multiple classifiers in order to enhance the performance of biometric person authentication systems. In this paper, the authors would like to argue that the core task of biometric person authentication is actually a multiple classifier problem as such: indeed, in order...

    Provided By Idiap Research Institute