WSN-Driven Posture Recognition and Correction Towards Basketball Exercise

Author:

Cai Xiangyang1

Affiliation:

1. Zhengzhou University of Industry Technology, China

Abstract

In order to enhance the daily training for basketball, this paper establishes a human posture estimation framework by using monocular camera and wireless sensor network. First, the daily basketball training images are collected by monocular camera and transmitted through wireless sensor network. Second, the collected images are processed by an observation and reasoning model which is based on component and graph reasoning. The basketball player's posture is depicted by the rotation invariant features of edge field. The extracted features are used to learn a boosting classifier as the observation model. The experimental results show that the posture recognition rate can achieve more than 88% for basketball player's action.

Publisher

IGI Global

Subject

Management of Technology and Innovation,Information Systems

Reference23 articles.

1. Sensors Technologies for Human Activity Analysis Based on SVM Optimized by PSO Algorithm.;M.Batool;2019 International Conference on Applied and Engineering Mathematics (ICAEM),2019

2. Bui, M. Q., Duong, V. H., Tai, T. C., & Wang, J. C. (2018, October). Depth Human Action Recognition Based on Convolution Neural Networks and Principal Component Analysis. In 2018 25th IEEE International Conference on Image Processing (ICIP) (pp. 1543-1547). IEEE.

3. Real-Time Human-Posture Recognition for Human-Drone Interaction Using Monocular Vision.;C.Cai;International Conference on Intelligent Robotics and Applications,2019

4. A convolutional neural network with feature fusion for real-time hand posture recognition.;S. F.Chevtchenko;Applied Soft Computing,2018

5. Sensor Fusion Basketball Shooting Posture Recognition System Based on CNN.;J.Fan;Journal of Sensors,2021

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