视频摘要的关键特征及新方法综述

Vinsent Paramanantham, Dr.S.S. Kumar
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引用次数: 0

摘要

在本文中,我们从各种文献中讨论了用于视频摘要/多视图视频摘要的在线、离线、监督、无监督、多视频和聚类方法的技术、算法和评估方法。我们在文献中研究了不同的技术,并描述了用于生成视频摘要的特征,包括评估方法、有监督的、无监督的、算法和使用的数据集。我们已经涵盖了对计算智能技术研究的新前沿的调查,如ANN(人工神经网络)和其他使用监督和无监督方法的VS进化算法。我们重点介绍了单视频、多视频摘要,其中包括文献中考虑的视频、音频和语义嵌入等特性。仔细的演示试图将性能与Precision, Recall, F-Score和手动方法进行比较,以评估VS。
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A Review on Key Features and Novel Methods for Video Summarization
In this paper, we discuss techniques, algorithms, evaluation methods used in online, offline, supervised, unsupervised, multi-video and clustering methods used for Video Summarization/Multi-view Video Summarization from various references. We have studied different techniques in the literature and described the features used for generating video summaries with evaluation methods, supervised, unsupervised, algorithms and the datasets used. We have covered the survey towards the new frontier of research in computational intelligence technique like ANN (Artificial Neural Network) and other evolutionary algorithms for VS using both supervised and unsupervised methods. We highlight on single, multi-video summarization with features like video, audio, and semantic embeddings considered for VS in the literature. A careful presentation is attempted to bring the performance comparison with Precision, Recall, F-Score, and manual methods to evaluate the VS.
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