Identifying Presentation Styles in Online Educational Videos
- Anitha Kannan ,
- Simon Baker
MSR-TR-2014-141 |
The rapid growth of online educational videos has resulted in huge redundancy. The same underlying content is often available in multiple videos with varying quality, presenter, and presentation style (slide show, whiteboard presentation, demo, etc). The fact that there are so many videos on the same content makes it important to retrieve videos that are attuned to user preferences. While there are several aspects that drive user engagement, we focus on the presentation style of the video. Based on a large scale manual study, we identify the 11 dominant presentation styles that typically employed. We propose a reference algorithm combining a set of 3-Way Decision Forests with probabilistic fusion and using a large set of image, face and motion features. We analyze our empirical results to provide understanding of the difficulties of the problem and to highlight directions for future research on this new application. We also make the data available.