Lecture Video Indexing and Retrieval Using Topic Keywords
In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1132190Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 688
 J. Adcock, M. Cooper, L. Denoue, H. Pirsiavash, and L. A. Rowe, “Talkminer: a lecture webcast search engine,” in Proceedings of the 18th ACM international conference on Multimedia. ACM, 2010, pp. 241–250.
 H. S. Haojin Yang and C. Meinel, “Lecture video indexing and analysis using video ocr technology,” in Signal-Image Technology and InternetBased Systems (SITIS), 2011 Seventh International Conference on. IEEE, 2011, pp. 54–61.
 A. S. Imran, L. Rahadianti, F. A. Cheikh, and S. Y. Yayilgan, “Semantic tags for lecture videos,” in Semantic Computing (ICSC), 2012 IEEE Sixth International Conference on. IEEE, 2012, pp. 117–120.
 D. D. Lee and H. S. Seung, “Algorithms for non-negative matrix factorization,” in Advances in neural information processing systems, 2001, pp. 556–562.
 S. Repp and M. Meinel, “Semantic indexing for recorded educational lecture videos,” in Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW’06). IEEE, 2006.
 H. Yang and C. Meinel, “Content based lecture video retrieval using speech and video text information,” IEEE Transactions On Learning Technologies, vol. 7, no. 2, pp. 142–154, 2014.
 H. Yang, C. Oehlke, and C. Meinel, “An automated analysis and indexing framework for lecture video portal,” in International Conference on WebBased Learning. Springer, 2012, pp. 285–294.
 H. Yang, M. Siebert, P. Luhne, H. Sack, and C. Meinel, “Automatic lecture video indexing using video ocr technology,” in Multimedia (ISM), 2011 IEEE International Symposium on. IEEE, 2011, pp. 111–116.