Investigating the Use of Autoencoders for Gait-based Person Recognition
| Author | Cheheb I. |
| Author | Al-Maadeed N. |
| Author | Al-Madeed S. |
| Author | Bouridane A. |
| Available date | 2019-11-03T11:47:38Z |
| Publication Date | 2018 |
| Publication Name | 2018 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2018 |
| Resource | Scopus |
| 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. � 2018 IEEE. |
| Sponsor | ACKNOWLEDGMENT 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. |
| Language | en |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Subject | Autoencoder Gait GEI |
| Type | Conference Paper |
| Pagination | 148 - 151 |
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