A new view-based approach to the representation and recognition of action is presented. The basis of the representation is a motion-history image (MHI) --- a static image where intensity is a function of the recency of motion in a sequence. We develop a recognition method which uses both binary and scalar-valued versions of the MHI as temporal templates to match against stored instances of actions. The method automatically performs temporal segmentation, is invariant to linear changes in speed, and runs in real-time on a standard platform. The applications we have begin to develop include simple room monitoring and an interactive game.