An automated human action recognition system may automatically recognize one or more actions of a human from 2D input image data representing a sequential series of input images of the human performing the one or more actions. Each input image may be from an unknown viewpoint. A computer memory system may contain 2D reference image data representing a plurality of reference actions which a human may perform. The 2D reference image data may include a plurality of linked sequences of key poses, including a linked sequence of key poses for each reference action. For each reference action, each key pose within the linked sequence of key poses for the reference action may consist essentially of 2D image data that is representative of a human figure performing the reference action at a selected point during the reference action. The timing of the selected points within the linked sequence of key poses for the reference action may be based on changes in the position of the human figure during the performance of the reference action. The linked sequence of key poses for the reference action may uniquely distinguish it from the linked sequence of key poses for all of the other reference actions. A computer processing system may be configured to determine which of the reference actions best matches the 2D input image data with no knowledge of the viewpoint of the 2D input image data.
Automated single viewpoint human action recognition by matching linked sequences of key poses