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Rock beats Scissor: SVM based gesture recognition with data gloves

Key:AMW+21
Author:Philipp Achenbach, Philipp Müller, Tobias Wach, Thomas Tregel, Stefan Göbel
Date:March 2021
Kind:In proceedings - use for conference & workshop papers
Book title:2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
Pages:617-622
ISBN:978-0-7381-4348-4/21/$31.00
Language:English
Research Area(s):Serious Games
Abstract:Hand gestures play an important role in human communication, particularly when auditory communication is limited. Akin to speech recognition, hand gesture recognition can therefore be a useful tool to facilitate communication and for more immersive computer interaction. In this paper, we examine the mobile recognition of hand gestures using data recorded with sensor gloves. We design a system based on Support Vector Machines (SVM), capable of recognizing 5 different hand gestures. In an experiment with 11 participants, we determine applicable hyperparameters based on performance on the training set which translates into 100% classification accuracy on the test set. In an additional practical experiment with 9 participants, our system achieves up to 98% in a personalized and up to 87.5% in a generalized model setting.
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