A Graph-based Ranking Approach to Extract Key-frames for Static Video Summarization

Saikat Chakraborty

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arXiv · 1911.13279

A Graph-based Ranking Approach to Extract Key-frames for Static Video Summarization

Saikat Chakraborty

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Abstract

Video abstraction has become one of the efficient approaches to grasp the content of a video without seeing it entirely. Key frame-based static video summarization falls under this category. In this paper, we propose a graph-based approach which summarizes the video with best user satisfaction. We treated each video frame as a node of the graph and assigned a rank to each node by our proposed VidRank algorithm. We developed three different models of VidRank algorithm and performed a comparative study on those models. A comprehensive evaluation of 50 videos from open video database using objective and semi-objective measures indicates the superiority of our static video summary generation method.

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Saikat Chakraborty. 2019-11-29. A Graph-based Ranking Approach to Extract Key-frames for Static Video Summarization. https://arxiv.org/abs/1911.13279

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