%Aigaion2 BibTeX export from Idiap Publications
%Thursday 04 December 2025 07:46:57 PM
@ARTICLE{sanders-pattreclett-24-16-2003,
author = {Sanderson, Conrad and Paliwal, Kuldip K.},
projects = {Idiap},
title = {{S}tructurally noise resistant classifier for multi-modal person verification},
journal = {Pattern Recognition Letters},
volume = {24},
number = {16},
year = {2003},
crossref = {sanders-rr-02-33},
ipdmembership={learning},
}
crossreferenced publications:
@TECHREPORT{sanders-rr-02-33,
author = {Sanderson, Conrad and Paliwal, Kuldip K.},
projects = {Idiap},
month = {9},
title = {{I}nformation {F}usion and {P}erson {V}erification Using {S}peech & {F}ace Information},
type = {Idiap-RR},
number = {Idiap-RR-33-2002},
year = {2002},
institution = {IDIAP},
abstract = {This report provides an overview of important concepts in the field of information fusion, followed by a review of literature pertaining to audio-visual person identification & verification. Several recent adaptive and non-adaptive techniques for reaching the verification decision (i.e., to accept or reject the claimant,',','),
based on audio and visual information, are evaluated in clean and noisy conditions on a common database using a text-independent setup. It is shown that in clean conditions all the non-adaptive approaches provide similar performance; in noisy conditions they exhibit deterioration in their performance. It is also shown that current adaptive approaches are either inadequate or utilize restrictive assumptions. A new category of classifiers is then introduced, where the decision surface is fixed but constructed to take into account the effects of noisy conditions, providing a good trade-off between performance in clean and noisy conditions.},
pdf = {https://publications.idiap.ch/attachments/reports/2002/rr02-33.pdf},
postscript = {ftp://ftp.idiap.ch/pub/reports/2002/rr02-33.ps.gz},
ipdmembership={learning},
}