Motion classification using distributional features of 3D skeleton data-Reference-Cited by-同舟云学术

Motion classification using distributional features of 3D skeleton data

Published:2023-11-30 Issue:6 Volume:30 Page:551-560
ISSN:2287-7843
Container-title:Communications for Statistical Applications and Methods
language:en
Short-container-title:Communications for Statistical Applications and Methods

Author:

Kim Woohyun¹,Kim Daeun¹,Park Kyoung Shin²,Lee Sungim¹

Affiliation:

1. Department of Statistics, Dankook University, Korea

2. Department of Computer Engineering, Dankook University, Korea

Funder

National Research Foundation of Korea

Ministry of Science and ICT, South Korea

Publisher

The Korean Statistical Society

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Finance,Modeling and Simulation,Statistics and Probability

Link

https://pdf.medrang.co.kr/CSAM/2023/030/CSAM030-06-551.pdf

Reference22 articles.

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2. Abnormal gait detection with RGB-D devices using joint motion history features

3. Cho B, Jang H, and Zhang B (2012). Motion recognition and classification using kinect sensor data. KIISE, 39, 318-320.

4. Cho K and Chen X (2014). Classifying and visualizing motion capture sequences using deep neural networks. Proceedings of 2014 International Conference on Computer Vision Theory and Applications, Lisbon, Portugal, 122-130.

5. Markerless Kinect-Based Hand Tracking for Robot Teleoperation

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