WIDAR3.0: WiFi-based Activity Recognition Dataset

This repository hosts the data and code for paper "Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi" published in ACM MobiSys 2019.This dataset includes the Channel State Information (CSI) data collected from commodity Wi-Fi devices for gestures and Body-coordinate Velocity Profile (BVP) data calculated by the algorithms from the above mentioned paper.Also included in this repository is the data for paper "GaitID: Robust WiFi Based Gait Recognition" published in Springer WASA 2020.Please stay tuned for further updates.Due to technical issues, please access our dataset homepage for download links: http://tns.thss.tsinghua.edu.cn/widar3.0/本仓库收录了发表于ACM MobiSys 2019的论文《基于Wi-Fi的零开销跨域手势识别（Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi）》对应的实验数据与代码。本数据集包含两类数据：一是由商用Wi-Fi设备采集的手势相关信道状态信息（Channel State Information，CSI）数据，二是由上述论文中的算法计算得到的身体坐标速度剖面（Body-coordinate Velocity Profile，BVP）数据。本仓库同时收录了发表于Springer WASA 2020的论文《GaitID：基于Wi-Fi的鲁棒步态识别（GaitID: Robust WiFi Based Gait Recognition）》对应的实验数据。敬请关注后续更新。因技术限制，请访问我们的数据集主页获取下载链接：http://tns.thss.tsinghua.edu.cn/widar3.0/

搜集汇总

背景与挑战

背景概述

WIDAR3.0是一个基于WiFi的活动识别数据集，包含从商用Wi-Fi设备收集的Channel State Information数据用于手势识别，以及计算得到的Body-coordinate Velocity Profile数据。该数据集支持手势识别和步态识别研究，相关成果发表于ACM MobiSys 2019和Springer WASA 2020论文，下载需通过指定主页链接。