4.6 Article

A Survey on Intelligent Gesture Recognition Techniques

Journal

IEEE ACCESS
Volume 10, Issue -, Pages 87135-87156

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3199358

Keywords

Gesture recognition; Artificial intelligence; Feature extraction; Face recognition; Three-dimensional displays; Solid modeling; Hidden Markov models; Artificial intelligence; deep learning; gesture recognition; machine learning

Funding

  1. EU ERDF
  2. Spanish Ministry of Economy and Competitiveness (MINECO) under AEI Project [TIN2017-83964-R]

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Gesture recognition is an ideal means of interaction that allows users to avoid contact with surfaces, making it safe and hygienic. Despite being researched for many years, it has not replaced keyboards and mice. Deep learning has made significant advancements in gesture recognition, offering the potential for it to become a viable option for daily user interaction.
Gesture recognition is an ideal means of interaction because it allows users not to have to make contact with any surface, which is a safe and hygienic means, especially in the pandemic situation that is occurring worldwide. However, gesture recognition is not a new discipline and it has been researched for many years but this type of interaction has not succeeded in replacing the keyboard and mouse. It is very useful to know about the advances that are being made with artificial intelligence in gesture recognition to be able to perform a more robust and reliable gesture recognition with a low response time. As it is, deep learning is being integrated into various areas to increase improvement in performance and one such area is artificial intelligence. In this way, there is the possibility that in the future the recognition of gestures will be a viable option as a means of daily interaction for the user and the main objective of this paper is to contribute to that process. For this reason, this study has analyzed 571 papers related to gesture recognition and artificial intelligence. This analysis has extracted relevant information related to scientific production, such as the most productive authors and journals or the most pertinent articles on the subject. Furthermore, we have developed our own model, which shows the relationship between the types of gesture recognition and the artificial intelligence techniques that have been applied for this task.

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