AUTOMATIC SUMMARIZATION OF BROADCASTED SOCCER VIDEOS WITH ADAPTIVE FAST-FORWARDING

When summarizing a video consisting of temporally continuous actions, e.g., surveillance videos or team-sport videos, fast-forwarding usually provides a better solution than content truncation to organize a semantically more complete and thus easily understandable story. Based on the resource allocation framework initially introduced in [1], we propose a fully automatic summarization system for broadcasted soccer videos, which supports adaptive fast-forwarding as well as content truncation. The proposed system involves two major contributions (i) an improved algorithm for refining the boundaries of far-view clips based on the extracted camera movement; (ii) a process to organize a summary by determining both the selected clips and their optimal fast-forwarding strategies, considering the scene-changing tempos of those clips and the given duration constraint. Experiments on real-life broad-casted soccer videos demonstrate the relevance and the efficiency of our proposed method.