This survey focuses on recognition performed by matching models of the three-dimensional
shape of the face, either alone or in combination with matching corresponding two …

Unimodal biometric systems have to contend with a variety of problems such as noisy data,
intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and …

Face recognition presents a challenging problem in the field of image analysis and
computer vision, and as such has received a great deal of attention over the last few years …

Government agencies are investing a considerable amount of resources into improving
security systems as result of recent terrorist events that dangerously exposed flaws and …

Cross-modality face recognition is an emerging topic due to the wide-spread usage of
different sensors in day-to-day life applications. The development of face recognition …

Multibiometric systems utilize the evidence presented by multiple biometric sources (eg, face
and fingerprint, multiple fingers of a user, multiple matchers, etc.) in order to determine or …

We present a fully automatic face recognition algorithm and demonstrate its performance on
the FRGC v2. 0 data. Our algorithm is multimodal (2D and 3D) and performs hybrid (feature …

An expression-invariant 3D face recognition approach is presented. Our basic assumption is
that facial expressions can be modelled as isometries of the facial surface. This allows to …

We report on the largest experimental study to date in multimodal 2D+ 3D face recognition,
involving 198 persons in the gallery and either 198 or 670 time-lapse probe images. PCA …

This paper proposes two multimodal fusion methods between brain and peripheral signals
for emotion recognition. The input signals are electroencephalogram and facial expression …