Vision-Based Hand Gesture Recognition for Human-Computer Interaction——A Survey

被引：2
|
作者：
GAO Yongqiang [1 ]
LU Xiong [1 ]
SUN Junbin [1 ]
TAO Xianglin [1 ]
HUANG Xiaomei [1 ]
YAN Yuxing [1 ]
LIU Jia [2 ]
机构：
[1] College of Automation Engineering, Nanjing University of Aeronautics and Astronautics
[2] School of Automation, Nanjing University of Information Science & Technology
来源：
Wuhan University Journal of Natural Sciences | 2020年 / 25卷 / 02期
基金：
中国国家自然科学基金; 中央高校基本科研业务费专项资金资助;
关键词：
vision-based gesture recognition; human-computer interaction; state-of-the-art; feature extraction;
D O I：
10.19823/j.cnki.1007-1202.2020.0020
中图分类号：
TP391.41 [];
学科分类号：
080203 ;
摘要：
Recently, vision-based gesture recognition(VGR) has become a hot research spot in human-computer interaction(HCI). Unlike other gesture recognition methods with data gloves or other wearable sensors, vision-based gesture recognition could lead to more natural and intuitive HCI interactions. This paper reviews the state-of-the-art vision-based gestures recognition methods, from different stages of gesture recognition process, i.e.,(1) image acquisition and pre-processing,(2) gesture segmentation,(3) gesture tracking,(4) feature extraction, and(5) gesture classification. This paper also analyzes the advantages and disadvantages of these various methods in detail. Finally, the challenges of vision-based gesture recognition in haptic rendering and future research directions are discussed.
引用
收藏
页码：169 / 184
页数：16
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