Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)

Enhancing Man-Machine Interaction with Markerless Motion Capture Technology

Authors
Haotian Zhang1, *
1Huaer Zizhu Academy, Shanghai, 200000, China
*Corresponding author. Email: hubery@usf.edu
Corresponding Author
Haotian Zhang
Available Online 23 September 2024.
DOI
10.2991/978-94-6463-512-6_24How to use a DOI?
Keywords
Markerless Motion Capture; Man-Machine Interaction; Image Processing
Abstract

This paper explores the use of Markerless Motion Capture technology in man-machine interaction, highlighting its potential to enhance the accuracy of computer-generated outputs. The primary objective of this study is to introduce Markerless Motion Capture and demonstrate its functionality in processing images. This technology captures photos of humans from different angles and analyzes these images to form various matrices. These matrices are then applied to different equations, resulting in numerous linear functions. The study utilizes the Markerless Motion Capture dataset for analysis. Experimental results indicate that Markerless Motion Capture significantly improves the clarity and efficiency of image input in man-machine interaction. This technology has diverse applications, including medical research and game development, among others. The findings suggest that Markerless Motion Capture can play a pivotal role in advancing various fields by providing precise and efficient image processing capabilities. In the future, it is anticipated that Markerless Motion Capture will be employed in an even broader range of applications, further demonstrating its versatility and impact. The study underscores the importance of adopting advanced image processing technologies to enhance human-computer interactions and drive innovation across multiple domains.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

Volume Title
Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
Series
Advances in Intelligent Systems Research
Publication Date
23 September 2024
ISBN
978-94-6463-512-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-512-6_24How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Haotian Zhang
PY  - 2024
DA  - 2024/09/23
TI  - Enhancing Man-Machine Interaction with Markerless Motion Capture Technology
BT  - Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
PB  - Atlantis Press
SP  - 210
EP  - 217
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-512-6_24
DO  - 10.2991/978-94-6463-512-6_24
ID  - Zhang2024
ER  -