In 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.

STRONGER: Simple TRajectory-based ONline GEsture Recognizer

Marco Emporio;Ariel Caputo;Andrea Giachetti
2021-01-01

Abstract

In 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.
978-3-03868-165-6
Mixed Reality, Gestures, Hand Tracking
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1052546
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