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Article http://dx.doi.org/10.26855/ea.2022.12.010

Human Skeleton Coordinate Pose Recognition

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Aodi Ding

Faculty of Applied Mathematics and Computer Sciences, Belarusian State University, Minsk, Belarus.

*Corresponding author: Aodi Ding

Published: January 12,2023

Abstract

The action of a character is composed of a 3D matrix of 20 three-dimensional coordinate points. The 20 points are the coordinates of the bones of the character's body. I divided the 1,000 data into four types of character actions. Now I use the Naive Bayes model and the linear Gaussian model to analyze the human skeleton coordinates, and judge which model is more suitable for human skeletal action prediction through the accuracy of the test set and the results of the confusion matrix. Of course, We can also use the character Actions are divided into more categories. We can capture specific actions to determine the behavioral state of the characters, and identify actions that endanger others. In the security field, this behavioral state of characters can help identify dangerous rioters so that we can take precautions in advance.

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How to cite this paper

Human Skeleton Coordinate Pose Recognition

How to cite this paper: Aodi Ding. (2022). Human Skeleton Coordinate Pose Recognition. Engineering Advances2(2), 194-197.

DOI: http://dx.doi.org/10.26855/ea.2022.12.010