基于视觉注意模型和HMM的足球视频语义分析

Semantic Analysis of Soccer Video Using Model of Visual Attention and HMM

HMM模型具有良好的适应性,可以自动学习,对预测随机时序数据性能良好。场景是足球视频的基本特征,场景的转换体现了足球视频的摄制、编辑模式,表现了足球视频的语义。提出了一种基于场景分析和HMM的视频语义分析框架,用于识别足球视频中的一些语义事件。为了克服以往基于主颜色和其他底层特征的视频场景分析中存在的较大误差,又提出基于视觉注意模型对足球视频中的场景进行分析。实验结果表明。

A hidden Markov model （HMM） has good adaptability, can automatically learn and adapts well when used in predicting temporal data. Changing of scenes in soccer video is a fundamental trait and manifests semantics of soccer video. In this paper, a new method based on scene classification and HMM is given to analyze semantics of video, detecting semantic events in soccer video. In order to solve the low accuracy and low robustness of scene classification based on traditional method, model of visual attention and gist of scene is used in classification of scenes of soccer video. The experimental results show higher efficiency and higher accuracy of our method in detecting free kick in soccer video.