Paper
26 November 2003 Video summarization: methods and landscape
Author Affiliations +
Abstract
The ability to summarize and abstract information will be an essential part of intelligent behavior in consumer devices. Various summarization methods have been the topic of intensive research in the content-based video analysis community. Summarization in traditional information retrieval is a well understood problem. While there has been a lot of research in the multimedia community there is no agreed upon terminology and classification of the problems in this domain. Although the problem has been researched from different aspects there is usually no distinction between the various dimensions of summarization. The goal of the paper is to provide the basic definitions of widely used terms such as skimming, summarization, and highlighting. The different levels of summarization: local, global, and meta-level are made explicit. We distinguish among the dimensions of task, content, and method and provide an extensive classification model for the same. We map the existing summary extraction approaches in the literature into this model and we classify the aspects of proposed systems in the literature. In addition, we outline the evaluation methods and provide a brief survey. Finally we propose future research directions based on the white spots that we identified by analysis of existing systems in the literature.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mauro Barbieri, Lalitha Agnihotri, and Nevenka Dimitrova "Video summarization: methods and landscape", Proc. SPIE 5242, Internet Multimedia Management Systems IV, (26 November 2003); https://doi.org/10.1117/12.515733
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CITATIONS
Cited by 16 scholarly publications.
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KEYWORDS
Video

Multimedia

Video surveillance

Visualization

Analytical research

Semantic video

Systems modeling

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