Event recognition in sport programs using low-level motion indices

A. Bonzanini, R. Leonardi, P. Migliorati
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引用次数: 27

Abstract

In this paper we present a semantic video indexing algorithm based on finite-state machines and low-level motion indices extracted from the MPEG compressed bit-stream. The problem of semantic video indexing is actually of great interest due to the wide diffusion of large video databases. In literature we can find many video indexing algorithms, based on various types of low-level features, but the problem of semantic indexing is less studied and surely it is a great challenging one. The proposed algorithm is an example of solution to the problem of finding a semantic relevant event (e.g., scoring of a goal in a soccer game) in case of specific categories of audio-visual programmes. The simulation results show that the proposed algorithm can effectively detect the presence of goals and other relevant events in sport programs.
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基于低水平运动指数的运动项目事件识别
本文提出了一种基于有限状态机和从MPEG压缩码流中提取的低级运动索引的语义视频索引算法。由于大型视频数据库的广泛分布,语义视频索引问题实际上引起了人们的极大兴趣。在文献中,我们可以找到许多基于各种类型的底层特征的视频索引算法,但对语义索引问题的研究较少,这无疑是一个巨大的挑战。所提出的算法是解决在特定类别的视听节目中寻找语义相关事件(例如,在足球比赛中进球)的问题的一个示例。仿真结果表明,该算法可以有效地检测出体育节目中是否存在目标和其他相关事件。
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