Motion analysis is an important component of surveillance, video annotation and many other applications. Current work focuses on the tracking of moving entities, the representation of their actions and the classification of sequences. A wide range of methods are available for the characterization and analysis of human activity. This work presents an original approach for the detailed characterization of activity in a video sequence. A novel framework for encoding and extracting representative, repeating segments of activities is presented, resulting in “Full Action Instances”. We focus on the analysis of human activities, however the proposed algorithm can be extended to more general categories of action that contains repetitive components, due to its general design.