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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 9, 2022.
Abstract: The overwhelming number of video uploads and downloads has made it incredibly difficult to find, gather, and archive videos. A static video summarization technique highlights an original video's significant points through a set of static keyframes as a video visual storyboard. The video visual storyboards are created as static video summaries that solve video processing-related issues like storage and retrieval. In this paper, a strategy for effectively summarizing static videos using the feature vectors, which are fractional coefficients of the transformed video frames, is proposed and evaluated. Four popular orthogonal transforms are deployed for generating feature vectors of video frames. The fractional coefficients of transformed video frames taken as 25 percent, 6.25 percent, and 1.5625 percent of full 100 percent transformed coefficients are considered to form video visual storyboards. The proposed method uses the benchmark video datasets Open Video Project (OVP) and SumMe to validate the performance, containing user summaries (storyboards). These video summaries created using the proposed method are evaluated using percentage accuracy and matching rate.
Ashvini Tonge and Sudeep D. Thepade, “Creating Video Visual Storyboard with Static Video Summarization using Fractional Energy of Orthogonal Transforms” International Journal of Advanced Computer Science and Applications(IJACSA), 13(9), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130931
@article{Tonge2022,
title = {Creating Video Visual Storyboard with Static Video Summarization using Fractional Energy of Orthogonal Transforms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130931},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130931},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {9},
author = {Ashvini Tonge and Sudeep D. Thepade}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.