A Logic Framework for Sports Video Summarization Using Text-Based Semantic Annotation

Abstract

Detection of semantic events in sports videos is an essential step towards video summarization. A large volume of research has been conducted for automatic semantic event detection and summarization of sports videos. In this paper we present a novel sports video summarization framework using a combination of text, video and logic analysis. Parse trees are used to analyze structured and free-style text webcasting of sports games and extract the game?s semantic events, such as goals and penalties in soccer games. Semantic events are then hierarchically arranged before being passed to a logic processing engine. The logic engine receives the summary preferences from the user and subsequently parses the event hierarchy to generate the game?s summary according to the user?s preferences. The proposed framework was applied to both soccer and basketball videos. We achieved an average accuracy of 98.6% and 100% on soccer and basketball videos, respectively.