This paper presents an approach to the recognition of human gestures in the context of the “Seamless” project “”. In the project, an environment is set up where data collected by IoT sensors can be navigated through gesture recognition algorithms and through virtual reality tools . The aim of recognizing human gestures in Seamless is to give commands through a wearable control device. The paper presents outlines the Seamless project and then concentrates on our approach to algorithms to understand a set of gestures using Machine Learning. The employed model and the results are illustrated.

Gesture Recognition for Navigation in Multi-Dimensional Data

M. Fugini;J. Finocchi;
2020

Abstract

This paper presents an approach to the recognition of human gestures in the context of the “Seamless” project “”. In the project, an environment is set up where data collected by IoT sensors can be navigated through gesture recognition algorithms and through virtual reality tools . The aim of recognizing human gestures in Seamless is to give commands through a wearable control device. The paper presents outlines the Seamless project and then concentrates on our approach to algorithms to understand a set of gestures using Machine Learning. The employed model and the results are illustrated.
28th IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2020, Basque Coast – Bayonne, FranceJune 12-14, 2019. IEEE 2019
Gesture Recognition, Human-Machine Interaction, Inertial Measurement Unit, Dynamic Time Warping, Supervised Machine Learning.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1141040
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