Shot Segmentation Based on Von Neumann Entropy for Key Frame Extraction

Fuente: arXiv
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Autores principales: Zhang, Xueqing, Fu, Di, Liu, Naihao
Formato: Preprint
Publicado: 2024
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author Zhang, Xueqing
Fu, Di
Liu, Naihao
author_facet Zhang, Xueqing
Fu, Di
Liu, Naihao
contents Video key frame extraction is important in various fields, such as video summary, retrieval, and compression. Therefore, we suggest a video key frame extraction algorithm based on shot segmentation using Von Neumann entropy. The segmentation of shots is achieved through the computation of Von Neumann entropy of the similarity matrix among frames within the video sequence. The initial frame of each shot is selected as key frames, which combines the temporal sequence information of frames. The experimental results show the extracted key frames can fully and accurately represent the original video content while minimizing the number of repeated frames.
format Preprint
id arxiv_https___arxiv_org_abs_2408_15844
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Shot Segmentation Based on Von Neumann Entropy for Key Frame Extraction
Zhang, Xueqing
Fu, Di
Liu, Naihao
Computer Vision and Pattern Recognition
Information Theory
Video key frame extraction is important in various fields, such as video summary, retrieval, and compression. Therefore, we suggest a video key frame extraction algorithm based on shot segmentation using Von Neumann entropy. The segmentation of shots is achieved through the computation of Von Neumann entropy of the similarity matrix among frames within the video sequence. The initial frame of each shot is selected as key frames, which combines the temporal sequence information of frames. The experimental results show the extracted key frames can fully and accurately represent the original video content while minimizing the number of repeated frames.
title Shot Segmentation Based on Von Neumann Entropy for Key Frame Extraction
topic Computer Vision and Pattern Recognition
Information Theory
url https://arxiv.org/abs/2408.15844