2,354 research outputs found
Hybrid Template Update System for Unimodal Biometric Systems
Semi-supervised template update systems allow to automatically take into
account the intra-class variability of the biometric data over time. Such
systems can be inefficient by including too many impostor's samples or skipping
too many genuine's samples. In the first case, the biometric reference drifts
from the real biometric data and attracts more often impostors. In the second
case, the biometric reference does not evolve quickly enough and also
progressively drifts from the real biometric data. We propose a hybrid system
using several biometric sub-references in order to increase per- formance of
self-update systems by reducing the previously cited errors. The proposition is
validated for a keystroke- dynamics authentication system (this modality
suffers of high variability over time) on two consequent datasets from the
state of the art.Comment: IEEE International Conference on Biometrics: Theory, Applications and
Systems (BTAS 2012), Washington, District of Columbia, USA : France (2012
Polarimetric Thermal to Visible Face Verification via Self-Attention Guided Synthesis
Polarimetric thermal to visible face verification entails matching two images
that contain significant domain differences. Several recent approaches have
attempted to synthesize visible faces from thermal images for cross-modal
matching. In this paper, we take a different approach in which rather than
focusing only on synthesizing visible faces from thermal faces, we also propose
to synthesize thermal faces from visible faces. Our intuition is based on the
fact that thermal images also contain some discriminative information about the
person for verification. Deep features from a pre-trained Convolutional Neural
Network (CNN) are extracted from the original as well as the synthesized
images. These features are then fused to generate a template which is then used
for verification. The proposed synthesis network is based on the self-attention
generative adversarial network (SAGAN) which essentially allows efficient
attention-guided image synthesis. Extensive experiments on the ARL polarimetric
thermal face dataset demonstrate that the proposed method achieves
state-of-the-art performance.Comment: This work is accepted at the 12th IAPR International Conference On
Biometrics (ICB 2019
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