Formulating Team-Sport Video Summarization as a Resource Allocation Problem

We propose a flexible framework to summarize team-sport videos that have been originally produced for broadcast purposes. The framework is able to integrate both the knowledge about displayed content (e.g., level of interest, type of view, and so on), and the individual (narrative) preferences of the user. It builds on the partition of the original video sequence into independent segments, and creates local stories by considering multiple ways to render each segment. We discuss how to segment videos automatically based on production principles, and design parametric functions to evaluate the benefit of various local stories from a segment. Summarization by selection of local stories is then regarded as a resource allocation problem, and Lagrangian relaxation is performed to find the optimum. We investigate the efficiency of our framework by summarizing soccer, basketball and volleyball videos in our experiments.