Video Summarization

EasyChair Preprint 1181, version 1

Abstract

Video is one of the robust sources of information and the consumption of online and offline videos has reached an unprecedented level in the last few years. A fundamental challenge of extracting information from videos is a viewer has to go through the complete video to understand the context, as opposed to an image where the viewer can extract information from a single frame. In this project, we attempt to employ different Algorithmic methodologies including local features and deep neural networks along with multiple clustering methods to find an effective way of summarizing a video by interesting keyframe extraction.

Keyphrases: Clustering, VSUMM, Videos, computer vision, deep learning, summary, video summarization

@booklet{EasyChair:1181,
  author    = {Shruti Jadon and Mahmood Jasim},
  title     = {Video Summarization},
  howpublished = {EasyChair Preprint 1181},
  year      = {EasyChair, 2019}}