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Overview of multimodal techniques for the characterization of sport programs

机译:体育课程表征的多模式技术概述

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The problem of content characterization of sports videos is of great interest because sports video appeals to large audiences and its efficient distribution over various networks should contribute to widespread usage of multimedia services. In this paper we analyze several techniques proposed in literature for content characterization of sports videos. We focus this analysis on the typology of the signal (audio, video, text captions, ...) from which the low-level features are extracted. First we consider the techniques based on visual information, then the methods based on audio information, and finally the algorithms based on audio-visual cues, used in a multi-modal fashion. This analysis shows that each type of signal carries some peculiar information, and the multi-modal approach can fully exploit the multimedia information associated to the sports video. Moreover, we observe that the characterization is performed either considering what happens in a specific time segment, observing therefore the features in a "static" way, or trying to capture their "dynamic" evolution in time. The effectiveness of each approach depends mainly on the kind of sports it relates to, and the type of highlights we are focusing on.
机译:体育视频的内容表征问题具有很大的兴趣,因为体育视频吸引大量受众以及其对各种网络的有效分配应该有助于广泛使用多媒体服务。在本文中,我们分析了在体育视频内容表征文献中提出的几种技术。我们将此分析专注于提取低级功能的信号(音频,视频,文本标题,...)的类型。首先,我们考虑基于视觉信息的技术,然后基于音频信息的方法,最后是基于视听线索的算法,以多模态方式使用。该分析表明,每种类型的信号都带有一些特殊信息,并且多模态方法可以充分利用与运动视频相关联的多媒体信息。此外,我们观察到考虑特定时间段中发生的事情,因此观察到的表征,从而以“静态”方式观察,或者试图及时捕获其“动态”演变。每种方法的有效性主要取决于它涉及的那种运动,以及我们专注于的亮点类型。

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