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ISSN: 1536-1233
Stephan Sigg , National Institute of Informatics, Tokyo
Markus Scholz , Karlsruhe Institute of Technology, Karlsruhe
Shuyu Shi , National Institute of Informatics, Tokyo
Yusheng Ji , National Institute of Informatics, Tokyo
Michael Beigl , Karlsruhe Institute of Technology, Karlsruhe
We consider the detection of activities from non-cooperating individuals with features obtained on the Radio Frequency channel. Since environmental changes impact the transmission channel between devices, the detection of this alteration can be used to classify environmental situations. We identify relevant features to detect activities of non-actively transmitting subjects. In particular, we distinguish with high accuracy an empty environment or a walking, lying, crawling or standing person, in case-studies of an active, device-free activity recognition system with software defined radios. We distinguish between two cases in which the transmitter is either under the control of the system or ambient. For activity detection the application of one-stage and two-stage classifiers is considered. Apart from the discrimination of the above activities, we can show that a detected activity can also be localised simultaneously within an area of less than 1 meter radius.
Location-dependent and sensitive, Computer Applications, Mobile Applications, Pervasive computing, Information Technology and Systems, Information Interfaces and Representation (HCI), Sound and Music Computing, Signal analysis, synthesis, and processing, Computing Methodologies, Pattern Recognition, Applications, Signal processing
Stephan Sigg, Markus Scholz, Shuyu Shi, Yusheng Ji, Michael Beigl, "RF-Sensing of Activities From Non-Cooperative Subjects in Device-Free Recognition Systems Using Ambient and Local Signals", IEEE Transactions on Mobile Computing, vol. , no. , pp. 0, 5555, doi:10.1109/TMC.2013.28
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