Manifold Adaptive Kernel Semisupervised Discriminant Analysis for Gait Recognition
Joint Authors
Huang, Yuchun
Sun, Lijun
Wang, Ziqiang
Sun, Xia
Source
Advances in Mechanical Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-04
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
A manifold adaptive kernel semisupervised discriminant analysis algorithm for gait recognition is proposed in this paper.
Motivated by the fact that the nonlinear structure captured by the data-independent kernels (such as Gaussian kernel, polynomial kernel, and Sigmoid kernel) may not be consistent with the discriminative information and the intrinsic manifold structure information of gait image, we construct two graph Laplacians by using the two nearest neighbor graphs (i.e., an intrinsic graph and a penalty graph) to model the discriminative manifold structure.
We then incorporate these two graph Laplacians into the kernel deformation procedure, which leads to the discriminative manifold adaptive kernel space.
Finally, the discrepancy-based semi-supervised discriminant analysis is performed in the manifold adaptive kernel space.
Experimental results on the well-known USF HumanID gait database demonstrate the efficacy of our proposed algorithm.
American Psychological Association (APA)
Wang, Ziqiang& Sun, Xia& Sun, Lijun& Huang, Yuchun. 2013. Manifold Adaptive Kernel Semisupervised Discriminant Analysis for Gait Recognition. Advances in Mechanical Engineering،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-454427
Modern Language Association (MLA)
Wang, Ziqiang…[et al.]. Manifold Adaptive Kernel Semisupervised Discriminant Analysis for Gait Recognition. Advances in Mechanical Engineering No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-454427
American Medical Association (AMA)
Wang, Ziqiang& Sun, Xia& Sun, Lijun& Huang, Yuchun. Manifold Adaptive Kernel Semisupervised Discriminant Analysis for Gait Recognition. Advances in Mechanical Engineering. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-454427
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-454427