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XGest: Enabling Cross-Label Gesture Recognition with RF Signals

Published: 03 September 2021 Publication History

Abstract

Extensive efforts have been devoted to human gesture recognition with radio frequency (RF) signals. However, their performance degrades when applied to novel gesture classes that have never been seen in the training set. To handle unseen gestures, extra efforts are inevitable in terms of data collection and model retraining. In this article, we present XGest, a cross-label gesture recognition system that can accurately recognize gestures outside of the predefined gesture set with zero extra training effort. The key insight of XGest is to build a knowledge transfer framework between different gesture datasets. Specifically, we design a novel deep neural network to embed gestures into a high-dimensional Euclidean space. Several techniques are designed to tackle the spatial resolution limits imposed by RF hardware and the specular reflection effect of RF signals in this model. We implement XGest on a commodity mmWave device, and extensive experiments have demonstrated the significant recognition performance.

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  1. XGest: Enabling Cross-Label Gesture Recognition with RF Signals

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    Published In

    cover image ACM Transactions on Sensor Networks
    ACM Transactions on Sensor Networks  Volume 17, Issue 4
    November 2021
    403 pages
    ISSN:1550-4859
    EISSN:1550-4867
    DOI:10.1145/3472298
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 03 September 2021
    Accepted: 01 March 2021
    Revised: 01 February 2021
    Received: 01 December 2020
    Published in TOSN Volume 17, Issue 4

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    Author Tags

    1. RF sensing
    2. gesture recognition
    3. machine learning

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    • National Key R&D Program of China
    • NSFC

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