Rule-based Event Detection of Broadcast Baseball Videos Using Mid-level Cues
Rule-based Event Detection of Broadcast Baseball Videos Using Mid-level Cues
复制标题
使用中级提示对广播棒球视频进行基于规则的事件检测
DOI：
10.1109/icicic.2007.507
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
C. Kuo
中科院分区：
文献类型：
--
作者：
Mao;C. Hsieh;C. Kuo
本文提出了一个有效的和高效的事件检测系统的广播棒球视频。它将包括记分牌信息和镜头转换模式在内的中级线索集成到事件分类规则中。首先，一个简单的记分牌检测和识别方案的开发，从视频中提取的游戏状态。然后，设计镜头转换分类器来获得镜头转换模式。所提取的中级线索被用来开发基于贝叶斯信念网络的事件分类器。利用网络的推理结果，我们进一步推导出一组分类规则来识别棒球事件。规则集存储在查找表中，使得分类仅是简单的表查找操作。仿真结果表明，该方法对10个重要棒球事件的识别准确率为95%，召回率为89%，具有很好的应用前景。
This paper presents an effective and efficient event detection system for broadcast baseball videos. It integrates mid-level cues including scoreboard information and shot transition patterns into event classification rules. First, a simple scoreboard detection and recognition scheme is developed to extract the game status from videos. Then, a shot transition classifier is designed to obtain the shot transition patterns. The extracted mid-level cues are used to develop an event classifier based on a Bayesian belief network. Using the inference results of the network, we further derive a set of classification rules to identify baseball events. The set of rules is stored in a look-up table such that the classification is only a simple table look-up operation. The simulation results indicate that it identifies ten significant baseball events with 95% of precision rate and 89% of recall rate, which is very promising.