基于视觉的神经网络三维动态手势识别方法综述

doi:10.11896/jsjkx.230200205

Abstract

Abstract: Dynamic gesture recognition,as an important means of human-computer interaction,has received widespread attention.Among them,the visual-based recognition method has become the preferred choice for the new generation of human-computer interaction due to its convenience and low cost.Centered on artificial neural networks,this paper reviews the research progress of visual-based gesture recognition methods,analyzes the development status of different types of artificial neural networks in gesture recognition,investigates and summarizes the types and characteristics of data to be recognized and training datasets.In addition,through performance comparison experiments,different types of artificial neural networks are objectively evaluated,and the results are analyzed.Finally,based on the summary of the research content,the challenges and problems faced in this field are elaborated,and the development trend of dynamic gesture recognition technology is prospected.

Key words: Dynamic gesture recognition, Human-Computer interaction, Artificial neural networks, Convolutional neural network, Recurrent neural network, Attention mechanism, Hybrid neural network

CLC Number:

TP391

WANG Ruiping, WU Shihong, ZHANG Meihang, WANG Xiaoping. Review of Vision-based Neural Network 3D Dynamic Gesture Recognition Methods[J].Computer Science, 2024, 51(4): 193-208.

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