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Multi-view Gait Recognition Based on Motion Regression using Multilayer Perceptron

Kusakunniran, Worapan; Wu, Qiang; Zhang, Jian; Li, Hongdong

Description

It has been shown that gait is an efficient biometric feature for identifying a person at a distance. However, it is a challenging problem to obtain reliable gait feature when viewing angle changes because the body appearance can be different under the various viewing angles. In this paper, the problem above is formulated as a regression problem where a novel View Transformation Model (VTM) is constructed by adopting Multilayer Perceptron (MLP) as regression tool. It smoothly estimates gait...[Show more]

dc.contributor.authorKusakunniran, Worapan
dc.contributor.authorWu, Qiang
dc.contributor.authorZhang, Jian
dc.contributor.authorLi, Hongdong
dc.coverage.spatialIstanbul Turkey
dc.date.accessioned2015-12-10T22:57:17Z
dc.date.createdAugust 23-26 2010
dc.identifier.urihttp://hdl.handle.net/1885/60587
dc.description.abstractIt has been shown that gait is an efficient biometric feature for identifying a person at a distance. However, it is a challenging problem to obtain reliable gait feature when viewing angle changes because the body appearance can be different under the various viewing angles. In this paper, the problem above is formulated as a regression problem where a novel View Transformation Model (VTM) is constructed by adopting Multilayer Perceptron (MLP) as regression tool. It smoothly estimates gait feature under an unknown viewing angle based on motion information in a well selected Region of Interest (ROI) under other existing viewing angles. Thus, this proposal can normalize gait features under various viewing angles into a common viewing angle before gait similarity measurement is carried out. Encouraging experimental results have been obtained based on widely adopted benchmark database.
dc.publisherIEEE Computer Society
dc.relation.ispartofseriesInternational Conference on Pattern Recognition (ICPR 2010)
dc.sourceProceedings of the International Conference on Pattern Recognition (ICPR 2010)
dc.subjectKeywords: Benchmark database; Biometric features; Gait features; Gait recognition; Motion information; Multi layer perceptron; Multi-views; Region of interest; Regression problem; Similarity measurements; View transformations; Viewing angle; Biometrics; Multilayers
dc.titleMulti-view Gait Recognition Based on Motion Regression using Multilayer Perceptron
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2010
local.identifier.absfor080106 - Image Processing
local.identifier.ariespublicationu4334215xPUB549
local.type.statusPublished Version
local.contributor.affiliationKusakunniran, Worapan, University of New South Wales
local.contributor.affiliationWu, Qiang, University of Technology Sydney
local.contributor.affiliationZhang, Jian, University of New South Wales
local.contributor.affiliationLi, Hongdong, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage2186
local.bibliographicCitation.lastpage2189
local.identifier.doi10.1109/ICPR.2010.535
local.identifier.absseo899999 - Information and Communication Services not elsewhere classified
dc.date.updated2016-02-24T11:01:50Z
local.identifier.scopusID2-s2.0-78149481382
CollectionsANU Research Publications

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