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Hand Gesture Recognition Using in Intelligent Transportation

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Cognitive Systems and Signal Processing (ICCSIP 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1006))

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Abstract

Hand gesture recognition is important for intelligent transportation. In this paper, C3D neural networks and transfer learning related technologies are used to recognize the traffic police’s gestures recognition. Firstly, C3D algorithm is used to model the spatial and temporal information of the gesture. Then, external data set was used for training and the resulted model was saved. Finally, the model is fine-tuned with the idea of transfer learning, so that a good recognition rate can be achieved by training with a small amount of traffic police gesture video. The experimental results show efficacy of our method.

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Acknowledgement

This work was supported partly by the National Natural Science Foundation of China (Grant No. 61673192), the Fund for Outstanding Youth of Shandong Provincial High School (ZR2016JL023), and the Basic Scientific Research Project of Beijing University of Posts and Telecommunications (2018RC31).

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Authors and Affiliations

  1. Automation School, Beijing University of Posts and Telecommunications, Beijing, China

    Chao Yang & Jianqin Yin

Authors
  1. Chao Yang
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  2. Jianqin Yin
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Corresponding author

Correspondence to Jianqin Yin .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Fuchun Sun

  2. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Huaping Liu

  3. College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, China

    Dewen Hu

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Yang, C., Yin, J. (2019). Hand Gesture Recognition Using in Intelligent Transportation. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2018. Communications in Computer and Information Science, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-7986-4_5

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  • DOI: https://doi.org/10.1007/978-981-13-7986-4_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-7985-7

  • Online ISBN: 978-981-13-7986-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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