1. A computer-based method for classifying an observed composite action, wherein the observed composite action comprises a combination of simple actions, comprising the steps of: receiving image data representing the observed composite action; generating a feature vector from said image data; generating a plurality of baseline reference vectors by combining two or more representations of simple actions, wherein said representations of simple actions are stored in a computer storage device; preprocessing the feature vector to modify the feature vector towards a baseline reference vector to form a modified feature vector; comparing the plurality of baseline reference vectors to the modified feature vector; and classifying the combination of simple actions comprising the observed composite action as stored representations of simple actions which comprise a baseline reference vector having a highest correlation to the modified feature vector.