title: Robust Indoor Human Activity Recognition Using Wireless Signals.
abstract: Wireless signals-based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI) of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP) and access points (AP). First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions' CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO) signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM) based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.
authors.affiliation: School of Software, Dalian University of Technology, Dalian 116620, China. dlutwangyi@dlut.edu.cn.
authors.forename: Yi
authors.initials: Y
authors.lastname: Wang
authors.affiliation: School of Software, Dalian University of Technology, Dalian 116620, China. jiangxl@dlut.edu.cn.
authors.forename: Xinli
authors.initials: X
authors.lastname: Jiang
authors.affiliation: School of Software, Dalian University of Technology, Dalian 116620, China. caocao7066@outlook.com.
authors.forename: Rongyu
authors.initials: R
authors.lastname: Cao
authors.affiliation: School of Software, Dalian University of Technology, Dalian 116620, China. ssdutwxy@foxmail.com.
authors.forename: Xiyang
authors.initials: X
authors.lastname: Wang
mesh_terms: D000368:Aged; D006801:Humans; D009068:Movement; D059015:Wireless Technology
keywords: action recognition; channel state information; wireless sensing