A Two-Layer Graphical Model for Combined Video Shot and Scene Boundary Detection

M. Al-Hames, Stefan Zettl, F. Wallhoff, S. Reiter, Björn Schuller, G. Rigoll
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引用次数: 2

Abstract

In this work we present a novel two-layer hybrid graphical model for combined shot and scene boundary detection in videos. In the first layer of the model, low-level features are used to detect shot boundaries. The shot layer is connected to a higher layer that detects scene or chapter boundaries from semantic features. With this structure, the model optimises the alignment for both layers at the same time and the detection results are interconnected. Experimental results on real video data show, that both layers highly benefit from this sharing of information. Compared to a baseline threshold method with the same features, the F-measure result for the shot detection has been improved by 12.6% absolute. For the scene boundary detection, the result has been improved by more than 11% absolute
视频镜头与场景边界联合检测的二层图形模型
在这项工作中,我们提出了一种新的两层混合图形模型,用于视频中镜头和场景的联合边界检测。在模型的第一层,低级特征用于检测镜头边界。镜头层连接到从语义特征中检测场景或章节边界的更高层。利用这种结构,该模型同时优化了两层的对准,并且检测结果是相互关联的。在真实视频数据上的实验结果表明,两层都从这种信息共享中获益良多。与具有相同特征的基线阈值法相比,镜头检测的f值结果提高了12.6%。在场景边界检测方面,提高了11%以上的绝对精度
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