This paper presents and describes a soft computing based expert system for gesture recognition procedure, as a part of intelligent user interface of a mobile terminal. In the presented solution, a terminal includes three acceleration sensors positioned like xyz co-ordinate system in order to get three-dimensional (3D) acceleration vector, xyz. The 3D acceleration vector is, after Doppler spectrum definition, used as an input vector to a fuzzy reasoning unit of embedded expert system, which classifies gestures (time series of acceleration vectors). In the reasoning unit fuzzy rule aided method is used to classification. The method is compared to the fuzzy c-means classification with feature extraction, to the hidden Markov model (HMM) classification and SOM classification. Fuzzy methods classified successfully the test sets. The advantages of the fuzzy methods are computational effectiveness, simple implementation, lower data sample rate requirement and reliability. Moreover, fuzzy methods do not require training like SOM and HMM. Therefore, the methods can be applied to the real time systems where different gestures can be used, for example, instead of the keyboard functions. The computational effectiveness and low sample rate requirement also increases the operational time of device compared to computationally heavy HMM method. Furthermore, the easy implementation and reliability are important factors for the success of the new technology's spreading on the mass market of terminals.
|Journal||Expert Systems with Applications|
|Publication status||Published - 2004|
|MoE publication type||A1 Journal article-refereed|
- Gesture recognition
- User interface