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Accuracy vs. Speed Trade-Off in Detecting of Shots in Video Content for Abstracting Digital Video Libraries

机译:提取数字视频库中视频内容中的镜头检测中的精度与速度之间的权衡

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摘要

Two basic requirements for a digital video library to be "browsable" are a precisely indexed content and informative abstracts. Nowadays such solutions are not common in video search engines or generic digital video platforms, therefore, the authors suggest developing some computer applications resolving the problems of at least abstracts' creation. The abstracts cannot be constructed without a deep video content analysis, including some low level processing like a shot detection towards a video sequence segmented to a series of "camera takes". The presented method, aimed at a shot detection, deploys a concept of a Motion Factor (of frame transitions). The basic definition considers the motion factor as a very sudden peak of difference between two successive frames. In some specific areas, the intrashot motion factor may suppress the shot-boundary motion factor. In order to avoid misrecognition of both motion factors during a shot detection process a concept of a differential motion factor was implemented. The full-resolution algorithm achieves the accuracy of up to 80%, however, it is very time-consuming. The shot detection accuracy was measured including true and false shots detected as well as real shots that were bounded visually. The authors' research of a representative number of movies (from various categories) has revealed that the shot detection process can be accelerated up to 500 times without any significant deterioration of shot recognition accuracy. The shot detection algorithm was accelerated in a simple manner by two-dimensional reduction of a frame resolution (in pixels).
机译:数字视频库“可浏览”的两个基本要求是精确索引的内容和内容丰富的摘要。如今,这种解决方案在视频搜索引擎或通用数字视频平台中并不常见,因此,作者建议开发一些计算机应用程序,以解决至少摘要创建的问题。如果不进行深入的视频内容分析,包括对镜头序列进行一系列镜头拍摄等镜头检测的一些低水平处理,就无法构建摘要。所提出的针对镜头检测的方法采用了(帧过渡)运动因子的概念。基本定义将运动因子视为两个连续帧之间的非常突然的差异峰值。在某些特定区域中,镜头内运动因子可以抑制镜头边界运动因子。为了避免在镜头检测过程中误识别两个运动因子,实施了差分运动因子的概念。全分辨率算法可实现高达80%的精度,但是这非常耗时。测量了镜头检测的准确性,包括检测到的真假镜头以及视觉范围内的真实镜头。作者对代表性电影(来自不同类别)的研究表明,镜头检测过程最多可以加速500倍,而镜头识别精度没有任何明显的下降。通过二维降低帧分辨率(以像素为单位),以简单的方式加速了镜头检测算法。

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