Estimating signal-dependent noise (SDN)-based motion variations to enhance gesture recognition-Reference-Cited by-同舟云学术

Estimating signal-dependent noise (SDN)-based motion variations to enhance gesture recognition

Published:2021-11-25 Issue: Volume: Page:1-13
ISSN:0169-1864
Container-title:Advanced Robotics
language:en
Short-container-title:Advanced Robotics

Author:

Das Swagata¹^ORCID,Ishibashi Yuya¹,Minakata Mayuko¹,Kurita Yuichi¹^ORCID

Affiliation:

1. Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI

New Energy and Industrial Technology Development Organization

Publisher

Informa UK Limited

Subject

Computer Science Applications,Hardware and Architecture,Human-Computer Interaction,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/01691864.2021.2004920

Reference37 articles.

1. Gesture Recognition: A Survey

2. Yoshida G, Murao K, Terada T, et al. Method of determining training data for gesture recognition considering decay in gesture movements. International Conference on Pervasive Computing and Communications Workshops; IEEE; 2013. p. 14–19.

3. Murao K, Terada T. A motion recognition method by constancy-decision. International Symposium on Wearable Computers; IEEE; 2010. p. 1–4.

4. uWave: Accelerometer-based personalized gesture recognition and its applications

5. Yamato J, Ohya J, Ishii K. Recognizing human action in time-sequential images using hidden Markov model. Conference on Computer Vision and Pattern Recognition; Vol. 92, IEEE; 1992. p. 379–385.

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