Human Gait Recognition Based on Frontal-View Sequences Using Gait Dynamics and Deep Learning-Reference-Cited by-同舟云学术

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Human Gait Recognition Based on Frontal-View Sequences Using Gait Dynamics and Deep Learning

Published:2024 Issue: Volume:26 Page:117-126
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Deng Muqing¹^ORCID,Fan Zhuyao²,Lin Peng²,Feng Xiaoreng³

Affiliation:

1. School of Automation, Guangdong University of Technology, Guangzhou, China

2. Institute of Information and Control, Hangzhou Dianzi University, Hangzhou, China

3. Department of Orthopaedics and Traumatology, Queen Mary Hospital, The University of Hong Kong, Hong Kong

Funder

Natural Science Foundation of Guangdong Province

Guangzhou Basic and Applied Basic Research Project

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Media Technology,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10081323.pdf?arnumber=10081323

Reference49 articles.

1. Human gait recognition based on deterministic learning and knowledge fusion through multiple walking views

2. Associated Spatio-Temporal Capsule Network for Gait Recognition

3. On Learning Disentangled Representations for Gait Recognition

4. Frontal-view gait recognition by intra- and inter-frame rectangle size distribution

5. Front-view Gait Recognition

Cited by 8 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. GaitKeeper: An AI-Enabled Mobile Technology to Standardize and Measure Gait Speed;Sensors;2024-08-28

2. GaitHF: Enhancing Appearance-Based Gait Recognition through Height Fused Images;2024-06-21

3. GaitHF: Height Fused Gait Recognition;2024-06-11

4. HGANet-23: a novel architecture for human gait analysis based on deep neural network and improved satin bowerbird optimization;Signal, Image and Video Processing;2024-06-07

5. Multi-3d Pose Tracking Based on Multi-View Fusion Feature Correlationmulti-3d Pose Tracking Based on Multi-View Fusion Feature Correlation;2024

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