Generalized joint sparse representation for multimodal biometric fusion of heterogeneous features

Research output: Chapter in Book/Conference paperConference paper

1 Citation (Scopus)

Abstract

In this paper we introduce a novel multimodal biometric recognition system based on generalized sparse representations. In the recently proposed systems, with heterogeneous features (such as audio and video), the joint sparse optimization problem was addressed by bringing the features into the same dynamic range, such as normalizing the features into unitl2 norm. This is however not optimal, and such normalization may decrease the performance of that modality unimodally. We propose to solve the original joint sparse optimization problem by introducing scaling factors for different modalities, such that the modalities interact efficiently at the feature level. The sequence-dependent scaling factors are automatically calculated so that the mismatch between the sparse representations of different modalities is accounted for. In the case of audiovisual recognition system, our experiments on the challenging MOBIO database show that the proposed method outperforms the original joint sparsity-based system (96.8% vs 94.3% recognition rate). © 2018 IEEE.
Original languageEnglish
Title of host publication2018 IEEE International Workshop on Information Forensics and Security (WIFS)
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
DOIs
Publication statusPublished - 30 Jan 2019
Event2018 IEEE International Workshop on Information Forensics and Security - Hong Kong , China
Duration: 11 Dec 201813 Dec 2018
https://wifs2018.comp.polyu.edu.hk/
https://signalprocessingsociety.org/blog/wifs-2018-2018-ieee-international-workshop-information-forensics-and-security

Conference

Conference2018 IEEE International Workshop on Information Forensics and Security
Abbreviated titleWIFS 2018
CountryChina
CityHong Kong
Period11/12/1813/12/18
OtherIEEE International Workshop on Information Forensics and Security (WIFS) is a unique annual event which is technically co-sponsored by the IEEE Biometrics Council and IEEE Signal Processing Society. The 2018 edition of this workshop will be held in Hong Kong. WIFS is the unique workshop series organised by the IEEE Information Forensics and Security (IFS) Technical Committee of the IEEE Signal Processing Society. It's a major forum that brings researchers from related disciplines to discuss emerging challenges in different areas of information security and forensics, and share the latest results. This workshop serves to provide a high quality forum for advancing research and development efforts in a range of areas defining e-security and forensics.
Internet address

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