STRONGER: Simple TRajectory-based ONline GEsture Recognizer

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dc.contributor.authorEmporio, Marcoen_US
dc.contributor.authorCaputo, Arielen_US
dc.contributor.authorGiachetti, Andreaen_US
dc.contributor.editorFrosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanueleen_US
dc.date.accessioned2021-10-25T11:53:39Z
dc.date.available2021-10-25T11:53:39Z
dc.date.issued2021
dc.description.abstractIn this paper, we present STRONGER, a client-server solution for the online gesture recognition from captured hands' joints sequences. The system leverages a CNN-based recognizer improving current state-of-the-art solutions for segmented gestures classification, trained and tested for the online gesture recognition task on a recent benchmark including heterogeneous gestures. The recognizer provides good classification accuracy and a limited number of false positives on most of the gesture classes of the benchmark used and has been used to create a demo application in a Mixed Reality scenario using an Hololens 2 optical see through Head-Mounted Display with hand tracking capability.en_US
dc.description.sectionheadersAugmented and Virtual Reality
dc.description.seriesinformationSmart Tools and Apps for Graphics - Eurographics Italian Chapter Conference
dc.identifier.doi10.2312/stag.20211481
dc.identifier.isbn978-3-03868-165-6
dc.identifier.issn2617-4855
dc.identifier.pages109-117
dc.identifier.urihttps://doi.org/10.2312/stag.20211481
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/stag20211481
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectNeural networks
dc.subjectHuman
dc.subjectcentered computing
dc.subjectGestural input
dc.titleSTRONGER: Simple TRajectory-based ONline GEsture Recognizeren_US
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