Che, Xiaoyin; Yang, Haojin; Meinel, Christoph
Proceedings of 2015 International Conference on Advances in Web-Based Learning (ICWL2015)
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 �xed title position, will be �gured out and applied in the adaptive rounds to improve the outline quality. The result of our experiments shows that the general accuracy of the �nal lecture outline reaches 85%, which is about 13% higher than the static method.