IEEE Trans Cybern. 2013 Oct;43(5):1318-34. doi: 10.1109/TCYB.2013.2265378. Epub 2013 Jun 25.
With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers.
随着低成本微软 Kinect 传感器的发明，高分辨率深度和视觉（RGB）感应已经可以广泛使用。Kinect 传感器提供的深度和视觉信息的互补性为解决计算机视觉中的基本问题开辟了新的机会。本文对基于 Kinect 的计算机视觉算法和应用进行了全面的回顾。所审查的方法是根据可以通过 Kinect 传感器解决或增强的视觉问题的类型进行分类的。涵盖的主题包括预处理、目标跟踪和识别、人体活动分析、手势分析和室内 3D 映射。对于每种方法类别，我们概述了它们的主要算法贡献，并总结了它们与 RGB 对应方法相比的优缺点。最后，我们概述了该领域的挑战和未来的研究趋势。本文旨在为基于 Kinect 的计算机视觉研究人员提供一个教程和参考来源。
