Multimodal identity verification based on learning face and gait cues

Emdad Hossain, Girija Chetty

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

21 Citations (Scopus)


In this paper we propose a novel multimodal Bayesian approach based on PCA-LDA processing for person identification from low resolution surveillance video with cues extracted from gait and face biometrics. The experimental evaluation of the proposed scheme on a publicly available database [2] showed that the combined PCA-LDA face and gait features can lead to powerful identity verification and can capture the inherent multimodality in walking gait patterns and discriminate the identity from low resolution surveillance videos.

Original languageEnglish
Title of host publicationNeural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
Subtitle of host publicationLecture Notes in Computer Science
EditorsBL Lu, L Zhang, J Kwok
Number of pages8
EditionPART 3
ISBN (Electronic)9783642249655
ISBN (Print)9783642249648
Publication statusPublished - 2011
EventInternational Conference on Neural Information Processing ICONIP 2011 - Shanghai, Shanghai, China
Duration: 13 Nov 201117 Nov 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7064 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Neural Information Processing ICONIP 2011
Abbreviated titleICONIP 2011


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