Video Lecture Summarization System


Sujal Agrawal
Shubhangi Tirpude


Video summarization is a promising approach which provides Comprehensive summary of the video by defining the informative video contents. Video lectures, video diaries, video messages on social networks and videos in various domains are dominating various forms of information exchange. As per the Cisco Visual Networking Index: Forecast and Methodology, 2016-2021, by 2019 video will account for 80\% of all global Internet traffic, excluding P2P channels. Nowadays the Lecture videos are an increasingly important learning resource for education. However, the challenge of quickly finding the content of interest in a lecture video is a limitation of this system. Thus, we have developed a lightweight system which can summarize the video lecture to save time, and also easy to use for users. The implemented system is a chrome/browser extension, which works on the browser itself, and runs in the background of the lecture (Google Meet here). This extension lets the user download the whole lecture and the summary of the lecture, and also makes them uploaded on the G-drive.


How to Cite
Agrawal, S., & Tirpude, S. . (2022). Video Lecture Summarization System. International Journal of Next-Generation Computing, 13(5).


  1. Chadawar, J., Deshmukh, V., Kharade, S., Shelar, T., and Bhandare, N. 2021. Lecture summarization using video processing and automatic text summarization. In 2021 International Conference on Intelligent Technologies (CONIT). 1–4. DOI:
  2. Erkan, G. and Radev, D. R. 2004. Lexrank: Graph-based lexical centrality as salience in text summarization. Journal of artificial intelligence research 22, 457–479. DOI:
  3. Seneviratne, I., Perera, B., Fernando, R., Siriwardana, L., and Rajapaksha, U. 2020. Student and lecturer performance enhancement system using artificial intelligence. In 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS). 88–93. DOI:
  4. Srinivas, M., Pai, M. M., and Pai, R. M. 2016. An improved algorithm for video summarization–a rank based approach. Procedia Computer Science 89, 812–819. DOI:
  5. Vimalaksha, A., Vinay, S., and Kumar, N. S. 2019. Hierarchical mind map generation from video lectures. In 2019 IEEE Tenth International Conference on Technology for Education (T4E). 110–113. DOI:
  6. Vimalaksha, A., Vinay, S., Prekash, A., and Kumar, N. S. 2018. Automated summarization of lecture videos. In 2018 IEEE Tenth International Conference on Technology for Education (T4E). 126–129. DOI:
  7. Gupta, A. and Prabhat, P., 2022. Towards a resource efficient and privacy-preserving framework for campus-wide video analytics-based applications. Complex & Intelligent Systems, pp.1-16. DOI:
  8. Widyassari, A. P., Rustad, S., Shidik, G. F., Noersasongko, E., Syukur, A., Affandy, A., and Setiadi, D. R. I. M. 2022. Review of automatic text summarization techniques methods. Journal of King Saud University - Computer and Information Sciences 34, 4, 1029–1046. DOI: