Investigating the Use of Autoencoders for Gait-based Person Recognition

Cheheb, Ismahane, Al-Maadeed, Noor, Al-Madeed, Somaya and Bouridane, Ahmed (2018) Investigating the Use of Autoencoders for Gait-based Person Recognition. In: 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS). IEEE, pp. 148-151. ISBN 978-1-5386-7754-4

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/AHS.2018.8541447

Abstract

In 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.

Item Type: Book Section
Uncontrolled Keywords: Autoencoder, Gait, GEI
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 05 Jun 2019 14:34
Last Modified: 10 Oct 2019 18:31
URI: http://nrl.northumbria.ac.uk/id/eprint/39509

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