Advances in Vision-Based Gesture Recognition and Its Diverse Applications
- DOI
- 10.2991/978-94-6463-512-6_22How to use a DOI?
- Keywords
- Computer Vision Gesture Recognition Overview
- Abstract
With the rapid development of science and technology, gesture recognition has emerged as one of the most important methods of human-computer interaction. Among the various approaches to gesture recognition, vision-based methods have proven to be the most mature and widely adopted. Vision-based gesture recognition leverages advanced computer vision techniques and machine learning algorithms to interpret human gestures from visual data captured by cameras. This method allows for intuitive and natural interactions between humans and computers, enabling applications in a wide range of fields. From virtual reality and gaming to sign language interpretation and smart home controls, vision-based gesture recognition offers significant potential for enhancing user experiences. Its ability to provide touchless control and seamless interaction makes it a crucial component in the advancement of human-computer interfaces. As technology continues to evolve, vision-based gesture recognition is expected to play an increasingly pivotal role in creating more immersive and responsive interactive systems.
- 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 - Jidong Liu AU - Yehao Tan AU - Zhaohe Wu PY - 2024 DA - 2024/09/23 TI - Advances in Vision-Based Gesture Recognition and Its Diverse Applications BT - Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024) PB - Atlantis Press SP - 189 EP - 194 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-512-6_22 DO - 10.2991/978-94-6463-512-6_22 ID - Liu2024 ER -