Comparison of k-Means and Bayes classifiers for Human Body Motions Classification

This paper deals with a comparison of k-Means and Bayes classifiers designed for classification of the human body motions classification. The main task of this paper is to compare the performance and the reliability of classifiers. The presented work is a part of research of relations between brain and muscle activity. The sensing of body motions is based on standard DV camcorders system. The procedures have no negative impact to brain activity (the tracking does not affect the measured EEG signals). Presented paper includes the description of observing, discerning and parameterization procedures and the discussion of motion classification. The results of classification accuracy are the part of this paper.