Multimodal biometrics: An overview

By Arun A. Ross, Anil K. Jain. 2004

781 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Information Systems

In Signal Processing

Citations in the corpus

SphereFace: Deep Hypersphere Embedding for Face Recognition (2017, background): “However, learning features with this criterion is generally difficult because of the intrinsically large intra-class variation and high interclass similarity [21] that faces exhibit.”
Multimodal fusion vulnerability to non-zero effort (spoof) imposters (2010, background): “To better deal with the performance of a biometric system as well as hopefully diminishing the possibility of circumvention, the idea of using multi-biometric systems has gained popularity [2].”
Offline geometric parameters for automatic signature verification using fixed-point arithmetic (2005, background): “The fusion of both scores can be done by regarding the problem as a classification or a combination problem [8].”
Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition (2016, methodology): “Finally, in case of decision level fusion the final results of multiple classifiers are combined via techniques such as majority voting [1]–[3].”
Online finger-knuckle-print verification for personal authentication (2010, background): “In fact, in such a case the system works as a kind of multi-modal system with a single biometric trait but multiple units [40].”
Deep Face Recognition: A Survey (2018, background): “ll biometric and forensic tasks, such as distinguishing identical twins and matching faces before and after surgery [302]. A reliable solution is to consolidate multiple sources of biometric evidence [303]. These sources of information may correspond to different biometric traits (e.g., face + hand ”
DCT-Based Iris Recognition (2007, background): “As security becomes an issue of importance, biometrics [3], [4], [5] and iris recognition in particular are attracting great interest [6].”
Continuous User Authentication on Mobile Devices: Recent progress and remaining challenges (2016, background): “Such unimodal systems have to deal with some of the following inevitable problems [60]:”
Dissimilarity-based people re-identification and search for intelligent video surveillance (2013, background): “In principle, two main combination techniques can be exploited to this aim [114]:2”