research-article

Deep Unsupervised Key Frame Extraction for Efficient Video Classification

Authors:

Paolo RotaAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications and Applications, Volume 19, Issue 3

Article No.: 119, Pages 1 - 17

https://doi.org/10.1145/3571735

Published: 25 February 2023 Publication History

Abstract

Video processing and analysis have become an urgent task, as a huge amount of videos (e.g., YouTube, Hulu) are uploaded online every day. The extraction of representative key frames from videos is important in video processing and analysis since it greatly reduces computing resources and time. Although great progress has been made recently, large-scale video classification remains an open problem, as the existing methods have not well balanced the performance and efficiency simultaneously. To tackle this problem, this work presents an unsupervised method to retrieve the key frames, which combines the convolutional neural network and temporal segment density peaks clustering. The proposed temporal segment density peaks clustering is a generic and powerful framework, and it has two advantages compared with previous works. One is that it can calculate the number of key frames automatically. The other is that it can preserve the temporal information of the video. Thus, it improves the efficiency of video classification. Furthermore, a long short-term memory network is added on the top of the convolutional neural network to further elevate the performance of classification. Moreover, a weight fusion strategy of different input networks is presented to boost performance. By optimizing both video classification and key frame extraction simultaneously, we achieve better classification performance and higher efficiency. We evaluate our method on two popular datasets (i.e., HMDB51 and UCF101), and the experimental results consistently demonstrate that our strategy achieves competitive performance and efficiency compared with the state-of-the-art approaches.

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Index Terms

Deep Unsupervised Key Frame Extraction for Efficient Video Classification
1. Networks
  1. Network components
  2. Network types

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 19, Issue 3

May 2023

514 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3582886

Editor:
Abdulmotaleb El Saddik
Mohamed Bin Zayed University of Artificial Intelligence, UAE and University of Ottawa, Canada

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Publication History

Published: 25 February 2023

Online AM: 12 December 2022

Accepted: 06 November 2022

Revised: 17 September 2022

Received: 18 April 2022

Published in TOMM Volume 19, Issue 3

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