手势
计算机科学
人工智能
支持向量机
手势识别
多普勒效应
计算机视觉
雷达
多普勒雷达
模式识别(心理学)
特征提取
旋转(数学)
语音识别
电信
物理
天文
作者
Zhang Shimeng,Gang Li,Matthew Ritchie,Francesco Fioranelli,Hugh Griffiths
标识
DOI:10.1109/radar.2016.8059518
摘要
Dynamic hand gesture recognition is of great importance for human-computer interaction. In this paper, we present a method to discriminate the four kinds of dynamic hand gestures, snapping fingers, flipping fingers, hand rotation and calling, using a radar micro-Doppler sensor. Two micro-Doppler features are extracted from the time-frequency spectrum and the support vector machine is used to classify these four kinds of gestures. The experimental results on measured data demonstrate that the proposed method can produce a classification accuracy higher than 88.56%.
科研通智能强力驱动
Strongly Powered by AbleSci AI