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首页> 外文期刊>International journal of artificial intelligence and soft computing >Detection of hard cuts and gradual transitions from video using fuzzy logic
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Detection of hard cuts and gradual transitions from video using fuzzy logic

机译:使用模糊逻辑检测视频的硬切和渐变

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摘要

In this paper, we introduce a novel approach for the detection and classification of shot boundaries based on interval type-2 fuzzy logic. We consider fuzzy low level features (Fuzzy Histogram (FH) and Fuzzy Co-occurrence Matrix (FCM)) and evaluate a fuzzy rule base modelled by interval type-2 sets to detect cut boundaries. After detection of cuts, a recovery mechanism is used to reduce false positives caused by illumination variation (e.g., camera flash light). The fuzzy rules used for gradual transition form a unified approach to detect various types gradual transitions like dissolves, fades and wipes, by a single method. Test results indicate that very high precision and recall could be achieved for the test videos, particularly the recall value of gradual transitions.
机译:在本文中,我们介绍了一种基于区间2型模糊逻辑的镜头边界检测和分类的新方法。我们考虑了模糊的低级特征(模糊直方图(FH)和模糊共现矩阵(FCM)),并评估了由间隔类型2集建模的模糊规则库,以检测切割边界。在检测到切割后,将使用恢复机制来减少由照明变化(例如相机闪光灯)引起的误报。用于渐变的模糊规则形成一种统一的方法,可以通过一种方法检测各种类型的渐变,例如溶解,褪色和擦拭。测试结果表明,测试视频可以达到很高的精度和召回率,尤其是逐步过渡的召回值。

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