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Research on Sign Language Recognition Algorithm Based on Improved R(2+1)D
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- Sheng Yueqin
- School of Electrical Engineering and Automation, Henan Polytechnic University
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- Liu Qunpo
- School of Electrical Engineering and Automation, Henan Polytechnic University
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- Gao Ruxin
- School of Electrical Engineering and Automation, Henan Polytechnic University
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- Naohiko Hanajima
- College of Information and Systems, Muroran Institute of Technology
Description
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.
Journal
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- Proceedings of International Conference on Artificial Life and Robotics
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Proceedings of International Conference on Artificial Life and Robotics 27 424-427, 2022-01-20
ALife Robotics Corporation Ltd.
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Details 詳細情報について
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- CRID
- 1390291767550900480
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- ISSN
- 21887829
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- OpenAIRE
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- Abstract License Flag
- Disallowed
