Research on Sign Language Recognition Algorithm Based on Improved R(2+1)D

DOI
  • Sheng Yueqin
    School of Electrical Engineering and Automation, Henan Polytechnic University
  • Liu Qunpo
    School of Electrical Engineering and Automation, Henan Polytechnic University
  • Gao Ruxin
    School of Electrical Engineering and Automation, Henan Polytechnic University
  • Naohiko Hanajima
    College of Information and Systems, Muroran Institute of Technology

説明

Sign language recognition based on deep learning has advantages in processing large scale dataset. Most of them use 3D convolution, which is not conducive to optimization. In this paper, an improved R(2+1)D model is proposed for isolated word recognition. The model convolves the video frame sequence in space and time dimensions and optimizes the parameters respectively. Based on CELU activation function, the accuracy of sign language recognition is improved effectively. The validity of proposed algorithm is verified on CSL dataset.

収録刊行物

キーワード

詳細情報 詳細情報について

  • CRID
    1390291767550900480
  • DOI
    10.5954/icarob.2022.os5-4
  • ISSN
    21887829
  • 本文言語コード
    en
  • データソース種別
    • JaLC
    • Crossref
    • OpenAIRE
  • 抄録ライセンスフラグ
    使用不可

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