Achenbach, Philipp ; Müller, Philipp Niklas ; Wach, Tobias Alexander ; Tregel, Thomas ; Göbel, Stefan (2021)
Rock beats Scissor: SVM based gesture recognition with data gloves.
18th International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events. virtual Conference (22.-26.03.2021)
doi: 10.1109/PerComWorkshops51409.2021.9430962
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2021 |
| Autor(en): | Achenbach, Philipp ; Müller, Philipp Niklas ; Wach, Tobias Alexander ; Tregel, Thomas ; Göbel, Stefan |
| Art des Eintrags: | Bibliographie |
| Titel: | Rock beats Scissor: SVM based gesture recognition with data gloves |
| Sprache: | Englisch |
| Publikationsjahr: | 24 Mai 2021 |
| Verlag: | IEEE |
| Buchtitel: | 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) |
| Veranstaltungstitel: | 18th International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events |
| Veranstaltungsort: | virtual Conference |
| Veranstaltungsdatum: | 22.-26.03.2021 |
| DOI: | 10.1109/PerComWorkshops51409.2021.9430962 |
| Kurzbeschreibung (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. |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Serious Games |
| Hinterlegungsdatum: | 25 Jan 2023 10:55 |
| Letzte Änderung: | 28 Mär 2023 11:13 |
| PPN: | 506360687 |
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