A complete framework for temporal video segmentation

Ruxandra Tapu, T. Zaharia
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引用次数: 17

Abstract

In this paper we propose a complete high level segmentation algorithm of video flows into scenes. In the first stage of our implementation we detected shot boundaries using an enhanced graph partition method based on non-linear scale space filtering at reduce computational time. In the second phase we develop static summaries for each detected shot based on a leap extraction technique that selects a variable number of keyframes depending on the visual content variation. Finally, we propose an iterative, temporally constrained shot clustering technique that detects video scenes with an average precision and recall rates of 85% and 84%.
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一个完整的框架的时间视频分割
本文提出了一种完整的视频流进入场景的高级分割算法。在我们实现的第一阶段,我们使用基于非线性尺度空间滤波的增强图分割方法来检测镜头边界,从而减少了计算时间。在第二阶段,我们基于跳跃提取技术为每个检测到的镜头开发静态摘要,该技术根据视觉内容的变化选择可变数量的关键帧。最后,我们提出了一种迭代的、时间约束的镜头聚类技术,该技术检测视频场景的平均精度和召回率分别为85%和84%。
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