Lecture videos are becoming ubiquitous medium for e-learning process. E-lecturing has evolved more competent popular lectures. The extent of lecture video data on the World Wide Web is increasing fastly. Therefore, a most appropriate method for retrieving video within huge lecture video library is required. The text displayed in a lecture video is closely related to the lecture content. Therefore, it provides a valuable source for indexing and retrieving lecture video contents.
In the last decade e-lecturing has become more and more popular. E-lecturing has evolved more competent popular lectures. These videos consist of textual information on slides as well as in presenter’s speech. The amount of lecture video data on the World Wide Web (WWW) is growing rapidly. Therefore, a most appropriate method for retrieving video within huge lecture video library is required, a more efficient method for video retrieval in WWW or within large lecture video archives is urgently needed. The objective of the system is to retrieve a video on the basis of its contents rather than retrieving video according to its title and metadata description in order to provide an accurate result for the search query.
- FFMPEG - FFmpeg is a free software project that produces libraries and programs for handling multimedia data.
- Tesseract - Tesseract is an optical character recognition engine for various operating systems.
- OpenCV - OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision
- Django - Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.
Note: Please refer the project report for further information.