Sarma Debajit, Bhuyan M K
Department of Electronics and Electrical Engineering, IIT Guwahati, Guwahati, India.
SN Comput Sci. 2021;2(6):436. doi: 10.1007/s42979-021-00827-x. Epub 2021 Aug 29.
Hand gesture recognition is viewed as a significant field of exploration in computer vision with assorted applications in the human-computer communication (HCI) community. The significant utilization of gesture recognition covers spaces like sign language, medical assistance and virtual reality-augmented reality and so on. The underlying undertaking of a hand gesture-based HCI framework is to acquire raw data which can be accomplished fundamentally by two methodologies: sensor based and vision based. The sensor-based methodology requires the utilization of instruments or the sensors to be genuinely joined to the arm/hand of the user to extract information. While vision-based plans require the obtaining of pictures or recordings of the hand gestures through a still/video camera. Here, we will essentially discuss vision-based hand gesture recognition with a little prologue to sensor-based data obtaining strategies. This paper overviews the primary methodologies in vision-based hand gesture recognition for HCI. Major topics include different types of gestures, gesture acquisition systems, major problems of the gesture recognition system, steps in gesture recognition like acquisition, detection and pre-processing, representation and feature extraction, and recognition. Here, we have provided an elaborated list of databases, and also discussed the recent advances and applications of hand gesture-based systems. A detailed discussion is provided on feature extraction and major classifiers in current use including deep learning techniques. Special attention is given to classify the schemes/approaches at various stages of the gesture recognition system for a better understanding of the topic to facilitate further research in this area.
手势识别被视为计算机视觉中一个重要的探索领域，在人机交互（HCI）社区有各种各样的应用。手势识别的重要应用涵盖手语、医疗辅助以及虚拟现实-增强现实等领域。基于手势的人机交互框架的基本任务是获取原始数据，这基本上可以通过两种方法来完成：基于传感器的方法和基于视觉的方法。基于传感器的方法需要使用仪器或传感器真正连接到用户的手臂/手上以提取信息。而基于视觉的方案则需要通过静态/视频摄像头获取手势的图片或视频。在此，我们将主要讨论基于视觉的手势识别，并对手基于传感器的数据获取策略做一些介绍。本文概述了用于人机交互的基于视觉的手势识别的主要方法。主要主题包括不同类型的手势、手势采集系统、手势识别系统的主要问题、手势识别的步骤，如采集、检测和预处理、表示和特征提取以及识别。在此，我们提供了一份详细的数据库列表，并讨论了基于手势的系统的最新进展和应用。本文还对手势识别系统当前使用的特征提取和主要分类器进行了详细讨论，包括深度学习技术。为了更好地理解该主题以便于在该领域进行进一步研究，我们特别对手势识别系统各个阶段的方案/方法进行了分类。
