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Real-Time Sign Language Detection using Human Pose Estimation


Moryossef, Amit; Tsochantaridis, Ioannis; Aharoni, Roee; Ebling, Sarah; Narayanan, Srini (2020). Real-Time Sign Language Detection using Human Pose Estimation. arXiv.org 04637, University of Zurich.

Abstract

We propose a lightweight real-time sign language detectionmodel, as we identify the need for such a case in videoconferencing. Weextract optical flow features based on human pose estimation and, usinga linear classifier, show these features are meaningful with an accuracyof 80%, evaluated on the Public DGS Corpus. Using a recurrent modeldirectly on the input, we see improvements of up to 91% accuracy,whilestill working under 4ms. We describe a demo application to signlanguagedetection in the browser in order to demonstrate its usage possibility invideoconferencing applications.

Abstract

We propose a lightweight real-time sign language detectionmodel, as we identify the need for such a case in videoconferencing. Weextract optical flow features based on human pose estimation and, usinga linear classifier, show these features are meaningful with an accuracyof 80%, evaluated on the Public DGS Corpus. Using a recurrent modeldirectly on the input, we see improvements of up to 91% accuracy,whilestill working under 4ms. We describe a demo application to signlanguagedetection in the browser in order to demonstrate its usage possibility invideoconferencing applications.

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Additional indexing

Item Type:Working Paper
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Date:23 August 2020
Deposited On:17 Dec 2020 08:47
Last Modified:17 Dec 2020 13:30
Series Name:arXiv.org
ISSN:2331-8422
Additional Information:ECCV 2020 Sign Language Recognition, Translation & Production (SLRTP) Workshop 23.08.2020
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:https://arxiv.org/pdf/2008.04637.pdf
Related URLs:https://arxiv.org/abs/2008.04637

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Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)