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ERIC Number: ED560543
Record Type: Non-Journal
Publication Date: 2015-Jun
Pages: 8
Abstractor: As Provided
Reference Count: 19
Topic Transition in Educational Videos Using Visually Salient Words
Gandhi, Ankit; Biswas, Arijit; Deshmukh, Om
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015)
In this paper, we propose a visual saliency algorithm for automatically finding the topic transition points in an educational video. First, we propose a method for assigning a saliency score to each word extracted from an educational video. We design several mid-level features that are indicative of visual saliency. The optimal feature combination strategy is learnt from a Rank-SVM to obtain an overall visual saliency score for all the words. Second, we use these words and their saliency scores to find the probability of a slide being a topic transition slide. On a test set of 10 instructional videos (12 hours), the F-score of the proposed algorithm in retrieving topic-transition slides is 0.17 higher than that of Latent Dirichlet Allocation (LDA)-based methods. The proposed algorithm enables demarcation of an instructional video along the lines of "table of content"/"sections" for a written document and has applications in efficient video navigation. User studies also demonstrate statistically significant improvement in across-topic navigation using the proposed algorithm. [For complete proceedings, see ED560503.]
International Educational Data Mining Society. e-mail:; Web site:
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: International Educational Data Mining Society