A Review on Video Summarization Techniques

Authors

  • Trupti Deshbhakar  BE Student, Department of Computer Science of Engineering, Priyadarshini J.L College of Engineering, Nagpur, Maharashtra, India
  • Simran Meshram  BE Student, Department of Computer Science of Engineering, Priyadarshini J.L College of Engineering, Nagpur, Maharashtra, India
  • Nisha Wakodikar  BE Student, Department of Computer Science of Engineering, Priyadarshini J.L College of Engineering, Nagpur, Maharashtra, India
  • Pranali Wanjari  BE Student, Department of Computer Science of Engineering, Priyadarshini J.L College of Engineering, Nagpur, Maharashtra, India
  • Prof. A. P. Mohod  Assistant Professor, Department of Computer Science of Engineering, Priyadarshini J.L College of Engineering, Nagpur, Maharashtra, India

Keywords:

Component, Static Video Summarization, Video Skimming, Convolutional Neural Networks

Abstract

With the quick development of digital video technology, it is possible to upload large videos to YouTube or any other websites, record huge amount of data as news videos, sports videos, and lecture videos and surveillance videos etc. Storage, transfer and processing of video take considerably large amount of time. The user might not have adequate time to watch enter video before downloading or the user needs the search result of video to be quick and precise. In such cases the highlight or summary of the video makes search and indexing operations fast and user can view the highlight or summary of the video before downloading the video. Video summarization is short summary or highlights of the long video. This work is a detailed study on various video summarization techniques.

References

  1. Truong, B. T., & Venkatesh, S. (2007). Video abstraction: A systematic review and classification. ACM transactions on multimedia computing, communications, and applications (TOMM), 3(1), 3.
  2. Ajmal, M., Ashraf, M. H., Shakir, M., Abbas, Y., & Shah, F. A. (2012, September). Video summarization: techniques and classification. In International Conference on Computer Vision and Graphics (pp. 1-13). Springer, Berlin, Heidelberg.
  3. Brezeale, D., & Cook, D. J. (2008). Automatic video classification: A survey of the literature. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 38(3), 416-430.
  4. Money, A. G., & Agius, H. (2008). Video summarisation: A conceptual framework and survey of the state of the art. Journal of Visual Communication and Image Representation, 19(2), 121-143.
  5. Srinivas, M., Pai, M. M., & Pai, R. M. (2016). An Improved Algorithm for Video Summarization–A Rank Based Approach. Procedia Computer Science, 89, 812-819.
  6. Song, X., Sun, L., Lei, J., Tao, D., Yuan, G., & Song, M. (2016). Event- based large scale surveillance video summarization. Neurocomputing, 187, 66-74.
  7. Deepika, T., & Babu, D. P. S. (2007). Motion Detection In Real-Time Video Surveillance with Movement Frame Capture And Auto Record in International Journal of Innovative Research in Science. Engineering and Technology An ISO, 3297.
  8. Jadhav, M. P. S., & Jadhav, D. S. (2015). Video Summarization Using Higher Order Color Moments (VSUHCM). Procedia Computer Science, 45, 275-281.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2021-06-30

Issue

Volume 8, Issue 3, May-June-2021

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Trupti Deshbhakar, Simran Meshram, Nisha Wakodikar, Pranali Wanjari, Prof. A. P. Mohod "A Review on Video Summarization Techniques" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 3, pp.158-165, May-June-2021.