Compressive representation for device-free activity recognition with passive RFID signal strength

• Main Authors: YAO, Lina, SHENG, Quan Z., LI, Xue, GU, Tao, TAN, Mingkui, WANG, Xianzhi, WANG, Sen, RUAN, Wenjie
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Activity recognition; RFID; compressive sensing; subspace decomposition; feature selection; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/6000; https://ink.library.smu.edu.sg/context/sis_research/article/7003/viewcontent/Compressive_Representation_for_Device_Free_Activity_2018_TMC_RFID_av.pdf
• Institution: Singapore Management University

Understanding and recognizing human activities is a fundamental research topic for a wide range of important applications such as fall detection and remote health monitoring and intervention. Despite active research in human activity recognition over the past years, existing approaches based on comp...