Tang Gaopeng, Wu Tongning, Li Congsheng
China Academy of Information and Communications Technology, Beijing 100191, China.
Sensors (Basel). 2023 Aug 28;23(17):7478. doi: 10.3390/s23177478.
As a convenient and natural way of human-computer interaction, gesture recognition technology has broad research and application prospects in many fields, such as intelligent perception and virtual reality. This paper summarized the relevant literature on gesture recognition using Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar from January 2015 to June 2023. In the manuscript, the widely used methods involved in data acquisition, data processing, and classification in gesture recognition were systematically investigated. This paper counts the information related to FMCW millimeter wave radar, gestures, data sets, and the methods and results in feature extraction and classification. Based on the statistical data, we provided analysis and recommendations for other researchers. Key issues in the studies of current gesture recognition, including feature fusion, classification algorithms, and generalization, were summarized and discussed. Finally, this paper discussed the incapability of the current gesture recognition technologies in complex practical scenes and their real-time performance for future development.
作为一种便捷自然的人机交互方式,手势识别技术在智能感知、虚拟现实等诸多领域具有广阔的研究与应用前景。本文综述了2015年1月至2023年6月期间利用调频连续波(FMCW)毫米波雷达进行手势识别的相关文献。在该论文中,系统研究了手势识别中数据采集、数据处理及分类所涉及的广泛使用的方法。本文统计了与FMCW毫米波雷达、手势、数据集以及特征提取和分类中的方法与结果相关的信息。基于统计数据,我们为其他研究人员提供了分析和建议。总结并讨论了当前手势识别研究中的关键问题,包括特征融合、分类算法和泛化能力。最后,本文探讨了当前手势识别技术在复杂实际场景中的不足及其未来发展的实时性能。