基于自适应加速和事件聚类的视频摘要冗余去除

2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services Pub Date : 2008-05-07 DOI:10.1109/WIAMIS.2008.13

Emilie Dumont, B. Mérialdo

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引用次数: 3

摘要

在本文中，我们提出了一种新的方法来总结rush。我们的处理由几个步骤组成。首先，我们删除无用的内容，并根据动作活动动态加速视频，使每单位时间内的内容最大化。然后，将一秒视频片段聚类到相似聚类中。选择最重要的非冗余的镜头片段，使它们最大限度地覆盖这些相似簇。生成的摘要已通过与TRECVID活动评估具有强正相关的自动方法进行评估。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Redundancy Removing by Adaptive Acceleration and Event Clustering for Video Summarization

In this paper, we propose a novel approach to summarize rushes. Our processing is composed of several steps. First, we remove unusable content and we dynamically accelerate video according to motion activity to maximize the content per time unit. Then, one-second video segments are clustered into similarity clusters. The most important nonredundant pieces of shot are selected such that they maximize the coverage of those similarity clusters. The produced summaries have been evaluated by an automatic method with a strong positive correlation with the TRECVID campaign evaluation.

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来源期刊

2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services

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