An innovative unsupervised gait recognition based tracking system for safeguarding large-scale nature reserves in complex terrain

Author:

Zhou ChichunORCID,Guan Xiaolin,Yu Zhuohang,Shen Yao,Zhang Zhenyu,Gu Junjie

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference52 articles.

1. Andrie, R., Basuki, A., & Arai, K. (2011). A review of Chinese Academy of Sciences (CASIA) gait database as a human gait recognition dataset.

2. A multilevel paradigm for deep convolutional neural network features selection with an application to human gait recognition;Arshad;Expert Systems with Applications,2020

3. Coupled patch alignment for matching cross-view gaits;Ben;IEEE Transactions on Image Processing,2019

4. Chai, T., Li, A., Zhang, S., Li, Z., & Wang, Y. (2022). Lagrange Motion Analysis and View Embeddings for Improved Gait Recognition. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 20249-20258.

5. Why protect nature? Rethinking values and the environment;Chan;Proceedings of the national academy of sciences,2016

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