<?xml version="1.0" encoding="UTF-8"?>
<collection xmlns="http://www.loc.gov/MARC21/slim">
	<record>
		<datafield tag="980" ind1=" " ind2=" ">
			<subfield code="a">REPORT</subfield>
		</datafield>
		<datafield tag="970" ind1=" " ind2=" ">
			<subfield code="a">Wallace_Idiap-RR-28-2011/IDIAP</subfield>
		</datafield>
		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Inter-session Variability Modelling and Joint Factor Analysis for Face Authentication</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Wallace, Roy</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">McLaren, Mitchell</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">McCool, Chris</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Marcel, Sébastien</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">2D Face Authentication</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">Inter-session Variability Modelling</subfield>
		</datafield>
		<datafield tag="653" ind1="1" ind2=" ">
			<subfield code="a">Joint Factor Analysis</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/reports/2011/Wallace_Idiap-RR-28-2011.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
		</datafield>
		<datafield tag="088" ind1=" " ind2=" ">
			<subfield code="a">Idiap-RR-28-2011</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2011</subfield>
			<subfield code="b">Idiap</subfield>
		</datafield>
		<datafield tag="771" ind1="2" ind2=" ">
			<subfield code="d">August 2011</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">This paper applies inter-session variability modelling
and joint factor analysis to face authentication using Gaussian
Mixture Models. These techniques, originally developed
for speaker authentication, aim to explicitly model and
remove detrimental within-client (inter-session) variation
from client models. We apply the techniques to face authentication
on the publicly-available BANCA, SCface and MOBIO
databases. We propose a face authentication protocol
for the challenging SCface database, and provide the first
results on the MOBIO still face protocol. The techniques
provide relative reductions in error rate of up to 44%, using
only limited training data. On the BANCA database,
our results represent a 31% reduction in error rate when
benchmarked against previous work.</subfield>
		</datafield>
	</record>
</collection>