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Sensors 2017, 17(1), 6; doi:10.3390/s17010006

Cross View Gait Recognition Using Joint-Direct Linear Discriminant Analysis

1
Instituto Politécnico Nacional, ESIME Culhuacan, 04430 Coyoacán, CDMX, Mexico
2
Department of Computer Science, University of Warwick, CV4 7AL Coventry, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 2 November 2016 / Revised: 20 December 2016 / Accepted: 20 December 2016 / Published: 22 December 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [3419 KB, uploaded 22 December 2016]   |  

Abstract

This paper proposes a view-invariant gait recognition framework that employs a unique view invariant model that profits from the dimensionality reduction provided by Direct Linear Discriminant Analysis (DLDA). The framework, which employs gait energy images (GEIs), creates a single joint model that accurately classifies GEIs captured at different angles. Moreover, the proposed framework also helps to reduce the under-sampling problem (USP) that usually appears when the number of training samples is much smaller than the dimension of the feature space. Evaluation experiments compare the proposed framework’s computational complexity and recognition accuracy against those of other view-invariant methods. Results show improvements in both computational complexity and recognition accuracy. View Full-Text
Keywords: gait recognition; view-invariant methods; gait energy image (GEI); direct linear discriminant analysis (DLDA); KNN classifier gait recognition; view-invariant methods; gait energy image (GEI); direct linear discriminant analysis (DLDA); KNN classifier
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Portillo-Portillo, J.; Leyva, R.; Sanchez, V.; Sanchez-Perez, G.; Perez-Meana, H.; Olivares-Mercado, J.; Toscano-Medina, K.; Nakano-Miyatake, M. Cross View Gait Recognition Using Joint-Direct Linear Discriminant Analysis. Sensors 2017, 17, 6.

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