Automatic generation of effective video summaries

Sasongko, Johannes (2011) Automatic generation of effective video summaries. Masters by Research thesis, Queensland University of Technology.


As the popularity of video as an information medium rises, the amount of video content that we produce and archive keeps growing. This creates a demand for shorter representations of videos in order to assist the task of video retrieval. The traditional solution is to let humans watch these videos and write textual summaries based on what they saw. This summarisation process, however, is time-consuming. Moreover, a lot of useful audio-visual information contained in the original video can be lost. Video summarisation aims to turn a full-length video into a more concise version that preserves as much information as possible. The problem of video summarisation is to minimise the trade-off between how concise and how representative a summary is. There are also usability concerns that need to be addressed in a video summarisation scheme. To solve these problems, this research aims to create an automatic video summarisation framework that combines and improves on existing video summarisation techniques, with the focus on practicality and user satisfaction. We also investigate the need for different summarisation strategies in different kinds of videos, for example news, sports, or TV series. Finally, we develop a video summarisation system based on the framework, which is validated by subjective and objective evaluation. The evaluation results shows that the proposed framework is effective for creating video skims, producing high user satisfaction rate and having reasonably low computing requirement. We also demonstrate that the techniques presented in this research can be used for visualising video summaries in the form web pages showing various useful information, both from the video itself and from external sources.

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491 since deposited on 26 Aug 2011
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ID Code: 45473
Item Type: QUT Thesis (Masters by Research)
Supervisor: Tjondronegoro, Dian & Cai, Jinhai
Keywords: key frame, multimedia information retrieval, scene segmentation, shotboundary detection, video summarisation, video tagging
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Information Systems
Institution: Queensland University of Technology
Deposited On: 26 Aug 2011 00:07
Last Modified: 26 Aug 2011 00:07

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