Emporio, MarcoCaputo, ArielGiachetti, AndreaFrosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele2021-10-252021-10-252021978-3-03868-165-62617-4855https://doi.org/10.2312/stag.20211481https://diglib.eg.org:443/handle/10.2312/stag20211481In 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.Computing methodologiesNeural networksHumancentered computingGestural input10.2312/stag.20211481109-117