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In-Air Gesture Interaction: Real Time Hand Posture Recognition Using Passive RFID Tags
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).ORCID iD: 0000-0002-2763-8085
2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 94460-94472Article in journal (Refereed) Published
Abstract [en]

In-air gesture interaction enables a natural communication between a man and a machine with its clear semantics and humane mode of operation. In this paper, we propose a real-time recognition system on multiple gestures in the air. It uses the commodity off-the-shelf (COTS) reader with three antennas to detect the radio frequency (RF) signals of the passive radio frequency identification (RFID) Tags attached to the fingers. The idea derives from the crucial insight that the sequential phase profile of the backscatter RF signals is a reliable and well-regulated indicator insinuating space-time situation of the tagged object, which presents a close interdependency with tag's movements and positions. The KL divergence is utilized to extract the dynamic gesture segment by confirming the endpoints of the data flow. To achieve the template matching and classification, we bring in the dynamic time warping (DTW) and k-nearest neighbors (KNN) for similarity scores calculation and appropriate gesture recognition. The experiment results show that the recognition rates for static and dynamic gestures can reach 85% and 90%, respectively. Moreover, it can maintain satisfying performance under different situations, such as diverse antenna-to-user distances and being hidden from view by nonconducting obstacles.

Place, publisher, year, edition, pages
IEEE, 2019. Vol. 7, p. 94460-94472
Keywords [en]
Gesture recognition, radio frequency identification (RFID), phase
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-2419DOI: 10.1109/ACCESS.2019.2928318ISI: 000478676600025Scopus ID: 2-s2.0-85073915435Local ID: 30221OAI: oai:DiVA.org:mau-2419DiVA, id: diva2:1399172
Available from: 2020-02-27 Created: 2020-02-27 Last updated: 2024-02-06Bibliographically approved

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Malekian, Reza

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