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Scene Change Detection Using a Local Detection Tree and Clustering in Ubiquitous Environment

机译:在本地环境中使用局部检测树和群集进行场景变化检测

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Processing of video data is embossed very importantly in ubiquitous environment. This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit. In other words, the local decision tree method is used to detect local scenes from a cluster segmentation unit.
机译:在无处不在的环境中,视频数据的处理非常重要。提出了一种基于局部决策树和聚类的场景变化检测方法。局部决策树以比较检测到的场景与其相邻帧之间的差值之间的时间相似性分布的方式,检测其中出现局部场景的聚类边界,并将具有差分值的相似性的不间断的帧序列分组为聚类单元。 。换句话说,局部决策树方法用于从聚类分割单元中检测局部场景。

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