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Investigating the Use of Autoencoders for Gait-based Person Recognition

المؤلفCheheb I.
المؤلفAl-Maadeed N.
المؤلفAl-Madeed S.
المؤلفBouridane A.
تاريخ الإتاحة2019-11-03T11:47:38Z
تاريخ النشر2018
اسم المنشور2018 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2018
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/AHS.2018.8541447
معرّف المصادر الموحدhttp://hdl.handle.net/10576/12221
الملخصIn recent years, gait has been growing as a biometric for person recognition at a distance. However, factors such as view angles and carrying conditions often make this task challenging. This paper proposes a solution to this problem by modelling gait sequences using Gait Energy Images and then using sparse autoencoders to extract their features for recognition under different view angles. Experiments were carried out on the challenging CASIA B dataset, resulting in outstanding accuracy rates. � 2018 IEEE.
راعي المشروعACKNOWLEDGMENT This publication was made possible using a grant from the Qatar National Research Fund through National Priority Research Program (NPRP) No. 8-140-2-065. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Qatar National Research Fund or Qatar University.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعAutoencoder
Gait
GEI
العنوانInvestigating the Use of Autoencoders for Gait-based Person Recognition
النوعConference
الصفحات148 - 151
dc.accessType Abstract Only


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