Titlebook: Biometric Authentication; International ECCV 2 Massimo Tistarelli,Josef Bigun,Anil K. Jain Conference proceedings 2002 Springer-Verlag Berl

amenity

Jill G. de Villiers,Peter A. de Villiers from the feature vectors extracted through a bank of Gabor filters. The advantages of this method with respect to other well-know approaches are experimentally proved; in particular, our subspace approach effectively captures the intra-class variability, thus allowing to better discriminate between

Itinerant

Nausicaa Pouscoulous,Ira A. Noveckages: the first stage computes a set of image features that are based on moments extracted from orthogonal view video silhouettes of human walking motion; the second stage applies three methods of aggregating these image features over time to create the gait sequence features. Despite their simplici

发酵剂

https://doi.org/10.1057/9780230240780eir walking gait. Stride parameters (stride length and cadence) are functions of body height, weight, and gender. Previous work has demonstrated effective use of these biometrics for identification and verification of people. In this paper, we show that performance is significantly improved by using

Measured

根除

Language Acquisition and Syntactic Theory,er hand, bayesian approach for evidence analysis and forensic reporting perfectly suits the needs of the court and the forensic scientist. Inside this bayesian framework, any biometric system can be adapted to provide its results in the form of . (LR) (being so converted in a forensic identification

Mystic

配偶

mucous-membrane

Face Recognition Based on ICA Combined with FLDar Discriminant Analysis) was reported as lower than an ICA only based method. This research points out that (ICA+LDA) methods have not got a fair comparison for evaluating its recognition performance. In order to incorporate class specific information into ICA, we have employed FLD (Fisher Linear D

foreign

reperfusion

Fusion of LDA and PCA for Face Verificationsystem robustness can be increased by the fusion of different face verification algorithms. To the best of our knowledge, no face verification system tried exploiting the fusion of LDA and PCA. In our opinion, the apparent strong correlation of LDA and PCA, especially when frontal views are used and