Abstract
In this paper, we propose an automated adaptive solution to generate logical, accurate and detailed tree-structure outline for video-based online lectures, by extracting the attached slides and reconstructing their content. The proposed solution begins with slide-transition detection and optical character recognition, and then proceeds by a static method of analyzing the layout of single slide and the logical relations within the slides series. Some features about the under-processing slides series, such as a fixed title position, will be figured out and applied in the adaptive rounds to improve the outline quality. The result of our experiments shows that the general accuracy of the final lecture outline reaches 85 %, which is about 13 % higher than the static method.
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Notes
- 1.
The copyright of the example slides belongs to original authors: Mr. Paul Cockshott, Prof. Audun Jøsang & Prof. Thomas Neumann.
- 2.
The copyright of the example slides belongs to original authors: Prof. Rudi Studer, Mr. Paul Cockshott & Prof. Gil Rosenman.
- 3.
The lecture (ID = ‘id’) is in http://www.tele-task.de/archive/lecture/overview/id/.
- 4.
https://drive.google.com/folderview?id=0B13Cc1a7ebTufmV6WFRCbmxPYllxR3 hYNE1SRUtWN3hxZl9tdHBPaHU0THZwOXVpM29sZEE&usp=sharing.
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Che, X., Yang, H., Meinel, C. (2015). Adaptive E-Lecture Video Outline Extraction Based on Slides Analysis. In: Li, F., Klamma, R., Laanpere, M., Zhang, J., Manjón, B., Lau, R. (eds) Advances in Web-Based Learning -- ICWL 2015. ICWL 2015. Lecture Notes in Computer Science(), vol 9412. Springer, Cham. https://doi.org/10.1007/978-3-319-25515-6_6
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DOI: https://doi.org/10.1007/978-3-319-25515-6_6
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