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Dynamic gesture recognition based on feature fusion network and variant ConvLSTM

  • Published:2020-07-28 Issue:11 Volume:14 Page:2480-2486
  • ISSN:1751-9659
  • Container-title:IET Image Processing
  • language:en
  • Short-container-title:IET image process

Author:

Peng Yuqing12,Tao Huifang12ORCID,Li Wei12,Yuan Hongtao12,Li Tiejun3

Affiliation:

1. School of Artificial Intelligence, Hebei University of TechnologyTianjin300401People's Republic of China

2. Hebei Province Key Laboratory of Big Data CalculationTianjin300401People's Republic of China

3. School of Mechanical Engineering, Hebei University of TechnologyTianjin300401People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference40 articles.

1. Gesture recognition: a survey;Mitra S.;IEEE TSMCC,2007

2. Gesture and Thought

3. A review of Convolutional-Neural-Network-based action recognition

4. KöpüklüO. KöseN. RigollG.: ‘Motion fused frames: data level fusion strategy for hand gesture recognition’ 2018

5. Challenges in multimodal gesture recognition;Escalera S.;J. Mach. Learn. Res.,2016

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4. Dynamic gesture tracking and recognition algorithm based on deep learning;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

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