Summarization and Indexing of Human Activity Sequences

In order to summarize a video consisting of a sequence of different activities, there are three fundamental problems: tracking the objects of interest, detecting the activity change times and recognizing the new activity. This paper presents an algorithm for achieving all these three tasks simultaneously and presents results on how it can used for indexing and summarizing a real-life video sequence. Human activities are represented by a model for the dynamics of the shape of the human body contour. Measures are designed for detecting both gradual transitions and sudden changes between activity models.