Multi-view gait fusion for large scale human identification in surveillance videos

Emdad Hossain, Girija Chetty

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


In this paper we propose a novel multi-view feature fusion of gait biometric information in surveillance videos for large scale human identification. The experimental evaluation on low resolution surveillance video images from a publicly available database [1] showed that the combined LDA-MLP technique turns out to be a powerful method for capturing identity specific information from walking gait patterns. The multi-view fusion at feature level allows complementarity of multiple camera views in surveillance scenarios to be exploited for improvement of identity recognition performance.
Original languageEnglish
Title of host publicationInternational Conference on Advanced Concepts in intelligent Vision Systems (ACIVS 2012)
Subtitle of host publicationLecture Notes in Computer Science
EditorsJacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders, Pavel Zemcik
Place of PublicationCzech Republic
Number of pages12
ISBN (Electronic)9783642331404
ISBN (Print)9783642331398
Publication statusPublished - 2012
EventAdvances Concepts for Intelligent Vision System - Brno, Brno, Czech Republic
Duration: 4 Sept 2012 → …


ConferenceAdvances Concepts for Intelligent Vision System
Country/TerritoryCzech Republic
Period4/09/12 → …


Dive into the research topics of 'Multi-view gait fusion for large scale human identification in surveillance videos'. Together they form a unique fingerprint.

Cite this