发表刊物:IEEE Communication Letters
摘要:Recent years have witnessed the great potential of adopting Channel State Information (CSI) for human-computer interaction by gestures. However, most current solutions either depend on specialized hardware or demand priori learning of wireless signal patterns, which face critical downsides in availability, reliability and extensibility. Hence this letter presents AirDraw, a novel learning-free in-air handwriting system by passive gesture tracking using only three commodity WiFi devices. First, we denoise CSI measurements by the ratio between two close-by antennas, and further separate the refl
论文类型:文章
文献类型:J
卷号:24
页面范围:2652-2656
ISSN号:1089-7798
是否译文:否
收录刊物:SCI