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Regression Analysis for Gesture Recognition Using RFID Technology

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8456))

Abstract

The recognition of gestures performed by humans always attracted researchers that applied such algorithms in a broad range of disciplines. In particular, it was exploited on pervasive environments to enable simple communication with automation systems. In this paper, we present a novel gesture recognition algorithm that works under uncertainty. The algorithm is based on the tracking of passive RFID tags installed on everyday life objects. The method is able to perform the difficult task of segmentation and recognize basic directions within noisy dataset of positions. A set of tests was conducted in a realistic environment, and the results obtained are encouraging.

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Correspondence to Kevin Bouchard .

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© 2015 Springer International Publishing Switzerland

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Bouchard, K., Bouchard, B., Bouzouane, A. (2015). Regression Analysis for Gesture Recognition Using RFID Technology. In: Bodine, C., Helal, S., Gu, T., Mokhtari, M. (eds) Smart Homes and Health Telematics. ICOST 2014. Lecture Notes in Computer Science(), vol 8456. Springer, Cham. https://doi.org/10.1007/978-3-319-14424-5_13

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  • DOI: https://doi.org/10.1007/978-3-319-14424-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14423-8

  • Online ISBN: 978-3-319-14424-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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