2009 | OriginalPaper | Buchkapitel
Hidden Markov Models Implementation for Tangible Interfaces
verfasst von : Piero Zappi, Elisabetta Farella, Luca Benini
Erschienen in: Intelligent Technologies for Interactive Entertainment
Verlag: Springer Berlin Heidelberg
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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.