Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/11175
Title: What do you wish to see? A summarization system for movies based on user preferences
Authors: Kannan, R
Ghinea, G
Swaminathan, S
Keywords: Video summarization;Movie summarization;Video semantics;Personalization;User preferences
Issue Date: 2015
Publisher: Elsevier
Citation: Information Processing and Management, 51(3): 286 - 305, ( May 2015)
Abstract: Video summarization aims at producing a compact version of a full-length video while preserving the significant content of the original video. Movie summarization condenses a full-length movie into a summary that still retains the most significant and interesting content of the original movie. In the past, several movie summarization systems have been proposed to generate a movie summary based on low-level video features such as color, motion, texture, etc. However, a generic summary, which is common to everyone and is produced based only on low-level video features will not satisfy every user. As users' preferences for the summary differ vastly for the same movie, there is a need for a personalized movie summarization system nowadays. To address this demand, this paper proposes a novel system to generate semantically meaningful video summaries for the same movie, which are tailored to the preferences and interests of a user. For a given movie, shots and scenes are automatically detected and their high-level features are semi-automatically annotated. Preferences over high-level movie features are explicitly collected from the user using a query interface. The user preferences are generated by means of a stored-query. Movie summaries are generated at shot level and scene level, where shots or scenes are selected for summary skim based on the similarity measured between shots and scenes, and the user's preferences. The proposed movie summarization system is evaluated subjectively using a sample of 20 subjects with eight movies in the English language. The quality of the generated summaries is assessed by informativeness, enjoyability, relevance, and acceptance metrics and Quality of Perception measures. Further, the usability of the proposed summarization system is subjectively evaluated by conducting a questionnaire survey. The experimental results on the performance of the proposed movie summarization approach show the potential of the proposed system.
URI: http://www.sciencedirect.com/science/article/pii/S0306457314001113
http://bura.brunel.ac.uk/handle/2438/11175
DOI: http://dx.doi.org/10.1016/j.ipm.2014.12.001
ISSN: 0306-4573
Appears in Collections:Dept of Computer Science Research Papers

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