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 convex-hull approximation to solve a resource allocation problem. Subjective experiments are performed to demonstrate the relevance and efficiency of the proposed method.
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© 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Chen, F., De Vleeschouwer, C. (2013). Personalized Summarization of Broadcasted Soccer Videos with Adaptive Fast-Forwarding. In: Mancas, M., d’ Alessandro, N., Siebert, X., Gosselin, B., Valderrama, C., Dutoit, T. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 124. Springer, Cham. https://doi.org/10.1007/978-3-319-03892-6_1
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DOI: https://doi.org/10.1007/978-3-319-03892-6_1
Publisher Name: Springer, Cham
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