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Classification of Movies and Television Shows Using Motion

机译:影视节目的运动分类

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An innovative technique used for categorizing motion pictures and television shows based on motion activity is presented. First, scenes extracted from digitally stored movies and television programs are segmented into separate clips based on various editing effects such as hard cuts, fades and dissolves. Next,the initial frame of the sequence is automatically segmented into meaningful objects using color and texture features using any image segmentation algorithm chosen by the author. An object tracking algorithm utilizing motion is then applied to each Intra (I) frame and each Predicted (P) frame in the video sequence. Interesting objects undergoing the highest degree of motion are then automatically selected for additional analysis. The distance between corresponding objectpsilas centroids existing in adjacent frames is computed for each interesting object. These distances are then used in classifying the clip as being an action or non-action video.
机译:提出了一种基于运动活动对电影和电视节目进行分类的创新技术。首先,根据各种编辑效果(例如硬剪切,淡入淡出和溶解),将从数字存储的电影和电视节目中提取的场景分割成单独的剪辑。接下来,使用作者选择的任何图像分割算法,使用颜色和纹理特征将序列的初始帧自动分割为有意义的对象。然后,将利用运动的对象跟踪算法应用于视频序列中的每个Intra(I)帧和每个Predicted(P)帧。然后,将自动选择运动程度最高的有趣对象,以进行其他分析。对于每个感兴趣的对象,计算相邻帧中存在的相应对象的质心之间的距离。然后将这些距离用于将剪辑分类为动作视频或非动作视频。

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