Personalized summarization of broadcasted soccer videos with adaptive fast-forwarding

Abstract

We propose a hybrid personalized summarization framework that combines adaptive fast-forwarding and content truncation to generate comfortable and compact video summaries. We formulate video summarization as a discrete optimization problem, where the optimal summary is determined by adopting Lagrangian relaxation and convexhull approximation to solve a resource allocation problem. Subjective experiments are performed to demonstrate the relevance and efficiency of the proposed method. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2013.