Automated human gesture recognition is receiving significant research interest, with applications ranging from novel acquisition techniques to algorithms, data processing, and classification methodologies. This tutorial presents an overview of the fundamental components and basics of the current 3D optical image acquisition technologies for gesture recognition, including the most promising algorithms. Experimental results illustrate some examples of 3D integral imaging, which are compared to conventional 2D optical imaging. Examples of classifying human gestures under normal and degraded conditions, such as low illumination and the presence of partial occlusions, are provided. This tutorial is aimed at an audience who may or may not be familiar with gesture recognition approaches, current 3D optical image acquisition techniques, and classification algorithms and methodologies applied to human gesture recognition.

中文翻译：

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使用3D积分成像的自动人体手势识别基础：教程

自动化的人类手势识别正在引起广泛的研究兴趣，其应用范围从新颖的采集技术到算法，数据处理和分类方法。本教程概述了用于手势识别的当前3D光学图像采集技术的基本组件和基础，包括最有前途的算法。实验结果说明了3D积分成像的一些示例，并将这些示例与常规2D光学成像进行了比较。提供了在正常和降级条件（例如低照度和部分遮挡的存在）下对人的手势进行分类的示例。本教程的对象是可能熟悉或可能不熟悉手势识别方法，当前3D光学图像采集技术，