On the application of AAM-based systems in face recognition

Muhammad Aurangzeb Khan, Costas Xydeas, Hassan Ahmed

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

The presence of significant levels of signal variability in face-portrait type of images, due to differences in illumination, pose and expression, is generally been accepted as having an adverse effect on the overall performance of i) face modeling and synthesis (FM/S) and also on ii) face recognition (FR) systems. Furthermore, the dependency on such input data variability and thus the sensitivity, with respect to face synthesis performance, of Active Appearance Modeling (AAM), is also well understood. As a result, the Multi-Model Active Appearance Model (MM-AAM) technique [1] has been developed and shown to possess a superior face synthesis performance than AAM. This paper considers the applicability in FR applications of both AAM and MM-AAM face modeling and synthesis approaches. Thus, a MM-AAM methodology has been devised that is tailored to operate successfully within the context of face recognition. Experimental results show FR-MM-AAM to be significantly superior to conventional FR-AAM. © 2014 EURASIP.
Original languageEnglish
Title of host publication22nd European Signal Processing Conference, EUSIPCO 2014
PublisherIEEE
Pages2445-2449
Number of pages5
ISBN (Print)9780992862619
Publication statusPublished - 10 Nov 2014
Event22nd European Signal Processing Conference - Lisbon, Portugal
Duration: 1 Sept 20145 Sept 2014
Conference number: 109162

Publication series

NameEuropean Signal Processing Conference
PublisherIEEE
ISSN (Print)2219-5491

Conference

Conference22nd European Signal Processing Conference
Abbreviated titleEUSIPCO 2014
Country/TerritoryPortugal
CityLisbon
Period1/09/145/09/14

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