Paper Info
Title
A Novel Application of Universal Background Models for Periocular Recognition
Abstract
In recent years the focus of research in the fields of iris and face recognition has turned towards alternative traits to aid in the recognition process under less constrained acquisition scenarios. The present work assesses the potential of the periocular region as an alternative to both iris and face in such conditions. An automatic modeling of SIFT descriptors, using a GMM-based Universal Background Model method, is proposed. This framework is based on the Universal Background Model strategy, first proposed for speaker verification, extrapolated into an image-based application. Such approach allows a tight coupling between individual models and a robust likelihood-ratio decision step. The algorithm was tested on the UBIRIS. v2 and the MobBIO databases and presented state-of-the-art performance for a variety of experimental setups.
Year
DOI
Venue
2015
10.1007/978-3-319-27707-3_18
BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, BIOSTEC 2015
Keywords
Field
DocType
Biometrics,Iris segmentation,Unconstrained environment,Gradient flow,Shortest closed path
Speaker verification,Scale-invariant feature transform,Facial recognition system,Pattern recognition,Computer science,Artificial intelligence,Biometrics,Periocular Region,Machine learning
Conference
Volume
ISSN
Citations 
574
1865-0929
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
João C. Monteiro1383.83
Jaime S. Cardoso254368.74