Personal‐specific gait recognition based on latent orthogonal feature space-Reference-Cited by-同舟云学术

Personal‐specific gait recognition based on latent orthogonal feature space

Published:2021-02-22 Issue:1 Volume:3 Page:61-69
ISSN:2517-7567
Container-title:Cognitive Computation and Systems
language:en
Short-container-title:Cogn. comput. syst.

Author:

Zhou Quan¹^ORCID,Shan Jianhua¹,Fang Bin²^ORCID,Zhang Shixin¹,Sun Fuchun²,Ding Wenlong¹,Wang Chengyin¹,Zhang Qin³

Affiliation:

1. AnHui Province Key Laboratory of Special Heavy Load Robot Anhui University of Technology Ma Anshan China

2. Beijing National Research Center for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China

3. Huazhong University of Science and Technology China

Publisher

Institution of Engineering and Technology (IET)

Subject

Pharmacology (medical)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ccs2.12007

Reference20 articles.

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2. Karout H. et al.:Frequency content analysis of gait — vertical ground reaction force. In:2015 International Conference on Advances in Biomedical Engineering (ICABME) pp.53–56.IEEE (2015).https://doi.org/10.1109/ICABME.2015.7323249

3. Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges

4. The CMU motion of body (MoBo) database;Gross R.,2001

5. Zheng S. et al.:Robust view transformation model for gait recognition. In:Proceedings ‐ International Conference on Image Processing ICIP. 2073‐2076(2011).https://doi.org/10.1109/ICIP.2011.6115889

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