Gait Recognition with Various Data Modalities: A Review-Reference-Cited by-同舟云学术

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Gait Recognition with Various Data Modalities: A Review

Published:2022 Issue: Volume: Page:414-423
ISSN:0302-9743
Container-title:Biometric Recognition
language:
Short-container-title:

Author:

Li Wei,Song Jiwei,Liu Yao,Zhong Chen,Geng Li,Wang Wenfeng

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-20233-9_42

Reference47 articles.

1. Alobaidi, H., Clarke, N., Li, F., Alruban, A.: Real-world smartphone-based gait recognition. Comput. Secur. 113, 102557 (2022)

2. An, W., et al.: Performance evaluation of model-based gait on multi-view very large population database with pose sequences. IEEE Trans. Biometrics Behav. Ident. Sci. 2(4), 421–430 (2020)

3. Castro, F.M., Marín-Jiménez, M., Mata, N.G., Muñoz-Salinas, R.: Fisher motion descriptor for multiview gait recognition. Int. J. Pattern Recogn. Artif. Intell. 31(01), 1756002 (2017)

4. Chao, H., He, Y., Zhang, J., Feng, J.: Gaitset: regarding gait as a set for cross-view gait recognition. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 8126–8133 (2019)

5. Choi, S., Kim, J., Kim, W., Kim, C.: Skeleton-based gait recognition via robust frame-level matching. IEEE Trans. Inf. Forensics Secur. 14(10), 2577–2592 (2019)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Gait Analysis through Machine Learning Algorithms;2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC);2024-01-27

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