| Issue |
E3S Web Conf.
Volume 297, 2021
The 4th International Conference of Computer Science and Renewable Energies (ICCSRE'2021)
|
|
|---|---|---|
| Article Number | 01030 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202129701030 | |
| Published online | 22 September 2021 | |
Approach for Improving User Interface Based on Gesture Recognition
1 RITM ESTC/CED ENSEM, Hassan II University Casablanca Morocco
2 LTIM, FS Ben M’SIK, Hassan II University Casablanca Morocco
3 SSL ENSIAS, University Mohammed V Rabat Morocco
4 RITM ESTC/CED ENSEM, University Hassan II Casablanca Morocco
* Corresponding author: magrouni@gmail.com
Gesture recognition technology based on visual detection to acquire gestures information is obtained in a non-contact manner. There are two types of gesture recognition: independent and continuous gesture recognition. The former aims to classify videos or other types of gesture sequences that only contain one isolated gesture instance in each sequence (e.g., RGB-D or skeleton data). In this study, we review existing research methods of visual gesture recognition and will be grouped according to the following family: static, dynamic, based on the supports (Kinect, Leap…etc), works that focus on the application of gesture recognition on robots and works on dealing with gesture recognition at the browser level. Following that, we take a look at the most common JavaScript-based deep learning frameworks. Then we present the idea of defining a process for improving user interface control based on gesture recognition to streamline the implementation of this mechanism.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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