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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM40002

AESTHETIC DRIVEN VIDEO SUMMARIZATION

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM40002

Volume:

8 |

12 |

Dec 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM40002

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

STV

Shruthi T V

RR

Rahul R

MN

M Neha

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Abstract

Video summarization condenses long, monotonous videos into concise representations, retaining critical events, objects, and sequences while minimizing redundancy. This allows users to quickly extract insights without watching the entire footage, benefiting fields like entertainment, education, surveillance, and recommendation systems. By integrating object detection a deep learning technique for identifying and localizing objects into the summarization process, the approach enhances relevance and context-awareness. This fusion ensures more accurate and meaningful summaries compared to traditional methods.

KEYWORDS

Video summarization Object detection Automated summarization Surveillance Deep learning.

Cite This Article

Shruthi T V, Rahul R, M Neha, "AESTHETIC DRIVEN VIDEO SUMMARIZATION," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 12, Dec 2024. https://doi.org/10.55041/IJSREM40002

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Publication Date

12/21/2024

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Double-Blind Peer Review

Review Rounds: 2

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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