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AuthorRida I.
AuthorAl-Maadeed, Somaya.
AuthorBouridane A.
Available date2022-05-19T10:23:14Z
Publication Date2014
Publication NameProceedings of the International Conference on Microelectronics, ICM
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/ICM.2014.7071801
URIhttp://hdl.handle.net/10576/31151
AbstractThe performance of gait recognition systems are usually affected by clothing, carrying conditions, and other intraclass variations which are also referred to as covariates. This paper proposes a supervised feature selection method which is able to select relevant features for human recognition to mitigate the impact of covariates and hence improve the recognition performance. The proposed method is evaluated using CASIA Gait Database (Dataset B) and the experimental results suggest that our method yields attractive results when compared to similar ones.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectGait analysis
Microelectronics
Covariates
Feature selection methods
Gait database
Gait energy images
Gait recognition
Human recognition
Intra-class variation
Relevant features
Pattern recognition
TitleImproved gait recognition based on gait energy images
TypeConference Paper
Pagination40-43
Volume Number2015-March
dc.accessType Abstract Only


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