Results

**11 - 14**of**14**### Towards Explaining the Success (Or Failure) of Fusion in Biometric Authentication

, 2005

"... submitted for publication Abstract. Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extents in various real-life applications. A system that uses more than one behavioural and physiological characteristics to v ..."

Abstract
- Add to MetaCart

(Show Context)
submitted for publication Abstract. Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extents in various real-life applications. A system that uses more than one behavioural and physiological characteristics to verify whether a person is who he/she claims to be is called a multimodal biometric authentication system. Due to lack of large true multimodal biometric datasets, the biometric trait of a user from a database is often combined with another different biometric trait of yet another user, thus creating a so-called a chimeric user. In the literature, this practice is justified based on the fact that the underlying biometric traits to be combined are assumed to be independent of each other given the user. To the best of our knowledge, there is no literature that approves or disapproves such practice. We study this topic from two aspects: 1) by clarifying the mentioned independence assumption and 2) by constructing a pool of chimeric users from a pool of true modality matched users (or simply “true users”) taken from a bimodal database, such that the performance variability due to chimeric user can be compared with that due to true users. The experimental results suggest that for a large proportion of the experiments, such practice is indeed questionable. Biometric authentication is a

### FÉDÉRALE DE LAUSANNE

"... et de nationalité malaisienne acceptée sur proposition du jury: Prof. J.R. Mosig, président du jury Prof. H. Bourlard, Dr. S. Bengio, directeurs de thèse ..."

Abstract
- Add to MetaCart

et de nationalité malaisienne acceptée sur proposition du jury: Prof. J.R. Mosig, président du jury Prof. H. Bourlard, Dr. S. Bengio, directeurs de thèse

### EER of Fixed and Trainable Fusion Classifiers: A Theoretical Study with Application to Biometric Authentication Tasks

, 2005

"... submitted for publication Abstract. Biometric authentication is a process of verifying an identity claim using a person’s behavioural and physiological characteristics. Due to the vulnerability of the system to environmental noise and variation caused by the user, fusion of several biometric-enabled ..."

Abstract
- Add to MetaCart

(Show Context)
submitted for publication Abstract. Biometric authentication is a process of verifying an identity claim using a person’s behavioural and physiological characteristics. Due to the vulnerability of the system to environmental noise and variation caused by the user, fusion of several biometric-enabled systems is identified as a promising solution. In the literature, various fixed rules (e.g. min, max, median, mean) and trainable classifiers (e.g. linear combination of scores or weighted sum) are used to combine the scores of several base-systems. How exactly do correlation and imbalance nature of base-system performance affect the fixed rules and trainable classifiers? We study these joint aspects using the commonly used error measurement in biometric authentication, namely Equal Error Rate (EER). Similar to several previous studies in the literature, the central assumption used here is that the class-dependent scores of a biometric system are approximately normally distributed. However, different from them, the novelty of this study is to make a direct link between the EER measure and the fusion schemes mentioned. Both synthetic and real experiments (with as many as 512 fusion experiments carried out on the XM2VTS benchmark score-level fusion data sets) verify our proposed theoretical modeling of EER of the two families of combination scheme. In particular, it is found that weighted sum can provide the best generalisation performance when its weights are estimated correctly. It also has the additional advantage that score normalisation prior to fusion is not needed, contrary to the rest of fixed fusion rules. 2 IDIAP–RR 05-01 1

### How do correlation and . . .

, 2004

"... Combining multiple information sources such as subbands, streams (with diferent features) and multi modal data has shown to be a very promising trend, both in experiments and to some extend in real-life biometric authentication applications. Despite considerable efforts in fusions, there is a lack o ..."

Abstract
- Add to MetaCart

Combining multiple information sources such as subbands, streams (with diferent features) and multi modal data has shown to be a very promising trend, both in experiments and to some extend in real-life biometric authentication applications. Despite considerable efforts in fusions, there is a lack of understanding on the roles and effects of correlation and variance (of both the client and impostor scores of base-classifiers/experts). Often, scores are assumed to be independent. In this paper, we explicitly consider this factor using a theoretical model, called Variance Reduction-Equal Error Rate (VR-EER) analysis. Assuming that client and impostor scores are approximately Gaussian distributed, we showed that Equal Error Rate (EER) can be modeled as a function of F-ratio, which itself is a function of 1) correlation, 2) variance of base-experts and 3) difference of client and impostor means. To achieve lower EER, smaller correlation and average variance of base-experts, and larger mean difference are desirable. Furthermore, analysing any of these factors independently, e.g. focusing on correlation alone, could be miss-leading. Experimental results on the BANCA and XM2VTS multi-modal databases and NIST 2001 speaker verification database confirm our findings using VR-EER analysis. Furthermore, F-ratio is shown to be a valid criterion in place of EER as an evaluation criterion. We analysed four commonly encountered scenarios in biometric authentication which include fusing correlated/uncorrelated base-experts of similar/different performances. The analysis explains and shows that fusing systems of different performances is not always beneficial. One of the most important findings is that positive correlation "hurts" fusion while negative correlation (greater "diversity", which...