Abstract
Ubiquitous computing is a new era in the evolution of computers. After the mainframe and PC (personal computers) phases, the phase of ubiquitous computing device begins. In this paper, we implement and evaluate glove-based HCI (Human Computer Interaction) methods using fuzzy algorithm and neural network for post PC in the ubiquitous computing. Using glove, we implement hand gesture recognition systems for the wearable PC. One system uses combination of fuzzy algorithm and RDBMS (Relational Database Management System) module, the other system uses neural network. Both systems are implemented on the platform of minimized wearable computer (based on i.MX21). After implementation, we conduct some performance evaluation in the mobile condition. And then we discuss strength and weakness of each method. Finally, we suggest possible improvements methods for HCI based on the wearable computers in the mobile condition.
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© 2006 Springer-Verlag Berlin Heidelberg
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Shin, JH., Kim, JH., Hong, KS. (2006). Implementation and Performance Evaluation of Glove-Based HCI Methods: Gesture Recognition Systems Using Fuzzy Algorithm and Neural Network for the Wearable PC. In: Bloch, I., Petrosino, A., Tettamanzi, A.G.B. (eds) Fuzzy Logic and Applications. WILF 2005. Lecture Notes in Computer Science(), vol 3849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11676935_17
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DOI: https://doi.org/10.1007/11676935_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32529-1
Online ISBN: 978-3-540-32530-7
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