Abstract
Smart objects equipped with inertial sensors can recognize gestures and act as tangible interfaces to interact with smart environments. Hidden Markov Models (HMM) are a powerful tool for gesture recognition. Gesture recognition with HMM is performed using the forward algorithm. In this paper we evaluate the fixed point implementation of the forward algorithm for HMM to assess if this implementation can be effective on resource constraint devices such as the Smart Micrel Cube (SMCube). The SMCube is a tangible interfacet that embeds an 8-bit microcontroller running at 7.372 MHz. The complexity-performance trade off has been explored, and a discussion on the critical steps of the algorithm implementation is presented.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-642-02315-6_30
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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Zappi, P., Farella, E., Benini, L. (2009). Hidden Markov Models Implementation for Tangible Interfaces. In: Nijholt, A., Reidsma, D., Hondorp, H. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 9. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02315-6_29
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DOI: https://doi.org/10.1007/978-3-642-02315-6_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02314-9
Online ISBN: 978-3-642-02315-6
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