Mining temporal information and web-casting text for automatic sports event detection

Minh-Son Dao, N. Babaguchi
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引用次数: 5

Abstract

In this paper, the generic framework for automatically detecting event based on Allen temporal algebra and external text information support is presented. The motivation of the proposed method is (1) to relax the need of domain knowledge that requires significant human interference; and (2) to take into account the temporal information that has been paid less attention though it is critical to convey event meaning. In order to solve two these problems, in the proposed method, the temporal information is captured by presenting events as the temporal sequences using a lexicon of Allen-based non-ambiguous temporal patterns. These sequences are then used to mine temporal patterns with web-casting text supports by using technique of mining class association rules. Then, the results of previous steps are tailored to build the event detector. Thorough experimental results and comparisons that are carried on more than 30 hours of soccer video corpus captured at different broadcasters and conditions demonstrates that the proposed method meets two aforementioned motivations with high efficiency, effectiveness, and robustness.
基于时态信息挖掘和网络投播文本的体育赛事自动检测
本文提出了基于Allen时间代数和外部文本信息支持的事件自动检测通用框架。提出的方法的动机是:(1)放松对需要大量人为干预的领域知识的需求;(2)考虑到对事件意义传达至关重要但却不被重视的时间信息。为了解决这两个问题,在该方法中,通过使用基于allen的非模糊时间模式词典将事件表示为时间序列来捕获时间信息。然后利用类关联规则挖掘技术,利用这些序列挖掘具有网播文本支持的时态模式。然后,调整前面步骤的结果以构建事件检测器。对在不同广播公司和条件下捕获的30多个小时的足球视频语料库进行了深入的实验和比较,结果表明,所提出的方法以高效率、有效性和鲁棒性满足上述两个动机。
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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