Abstract
Nowadays, computer interaction is mostly done using dedicated devices. But gestures are an easy mean of expression between humans that could be used to communicate with computers in a more natural manner. Most of the current research on hand gesture recognition for Human-Computer Interaction rely on either the Neural Networks or Hidden Markov Models (HMMs). In this paper, we compare different approaches for gesture recognition and highlight the major advantages of each. We show that gestures recognition based on the Bio-mechanical characteristic of the hand provides an intuitive approach which provides more accuracy and less complexity.
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Parvini, F., McLeod, D., Shahabi, C., Navai, B., Zali, B., Ghandeharizadeh, S. (2009). An Approach to Glove-Based Gesture Recognition. In: Jacko, J.A. (eds) Human-Computer Interaction. Novel Interaction Methods and Techniques. HCI 2009. Lecture Notes in Computer Science, vol 5611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02577-8_26
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DOI: https://doi.org/10.1007/978-3-642-02577-8_26
Publisher Name: Springer, Berlin, Heidelberg
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