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Video summarization using deep learning techniques: a detailed analysis and investigation.

Parul Saini1, Krishan Kumar1, Shamal Kashid1

  • 1Department of Computer Science and Engineering, National Institute of Technology Uttarakhand, Srinagar Garhwal, Uttarakhand 246174 India.

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|June 26, 2023
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Summary
This summary is machine-generated.

This study analyzes deep learning for video summarization (VS), finding current methods inefficient for long videos. It suggests strategies to improve VS performance and identifies future research directions.

Keywords:
Critical information in videosEvent summarizationMultimedia analysisSurveillance systemsVideo analysis

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Multimedia Analysis

Background:

  • Video summarization (VS) is crucial for multimedia analysis.
  • Existing deep learning (DL) methods struggle with efficiency in processing long-duration videos.
  • Identifying and summarizing essential activities in videos remains a challenge.

Purpose of the Study:

  • To investigate the limitations of current deep learning approaches in video summarization.
  • To analyze the root causes of inefficiencies in processing and extracting information from long videos.
  • To propose viable strategies for improving video summarization techniques.

Main Methods:

  • Detailed analysis of various deep learning techniques for event detection and summarization.
  • Examination of keyframe selection, event categorization, and activity feature summarization.
  • Discussion of limitations in detecting low-activity events across public datasets.

Main Results:

  • Identified inefficiencies in deep learning-based video summarization for long videos.
  • Highlighted challenges in event detection, categorization, and summarization of multiple activities.
  • Discussed limitations related to low-activity event detection in deep networks.

Conclusions:

  • Current deep learning methods for video summarization require significant improvement for efficiency and accuracy.
  • Strategies for evaluating and enhancing video summaries are proposed.
  • Future research should focus on addressing identified limitations and exploring new DL strategies for VS.