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المؤلفRida I.
المؤلفAl-Maadeed, Somaya.
المؤلفBouridane A.
تاريخ الإتاحة2022-05-19T10:23:14Z
تاريخ النشر2014
اسم المنشورProceedings of the International Conference on Microelectronics, ICM
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/ICM.2014.7071801
معرّف المصادر الموحدhttp://hdl.handle.net/10576/31151
الملخصThe 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.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعGait analysis
Microelectronics
Covariates
Feature selection methods
Gait database
Gait energy images
Gait recognition
Human recognition
Intra-class variation
Relevant features
Pattern recognition
العنوانImproved gait recognition based on gait energy images
النوعConference Paper
الصفحات40-43
رقم المجلد2015-March
dc.accessType Abstract Only


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