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Evaluating and combining digital video shot boundary detection algorithms

机译:评估和组合数字视频镜头边界检测算法

摘要

The development of standards for video encoding coupled with the increased power of computing mean that content-based manipulation of digital video information is now feasible. Shots are a basic structural building block of digital video and the boundaries between shots need to be determined automatically to allow for content-based manipulation. A shot can be thought of as continuous images from one camera at a time. In this paper we examine a variety of automatic techniques for shot boundary detection that we have implemented and evaluated on a baseline of 720,000 frames (8 hours) of broadcast television. This extends our previous work on evaluating a single technique based on comparing colour histograms. A description of each of our three methods currently working is given along with how theyudare evaluated. It is found that although the different methods have about the same order of magnitude in terms of effectiveness, different shot boundaries are detected by the different methods. We then look at combining the three shot boundary detection methods to produce one output result and the benefits in accuracy and performance that this brought to our system. Each of the methods were changed from usinguda static threshold value for three unconnected methods to one using three dynamic threshold values for one connected method. In a final summing up we look at the future directions for this work.
机译:视频编码标准的发展以及更高的计算能力意味着基于内容的数字视频信息处理现在是可行的。镜头是数字视频的基本结构构建块,需要自动确定镜头之间的边界,以允许基于内容的操作。一次拍摄可以看作一次来自一台摄像机的连续图像。在本文中,我们研究了多种自动镜头边界检测技术,这些技术已经在广播电视的720,000帧(8小时)的基线上实现和评估。这扩展了我们先前基于比较颜色直方图评估单个技术的工作。给出了我们目前正在使用的三种方法的描述以及它们如何评估。已经发现,尽管不同的方法在有效性方面具有大约相同的数量级,但是通过不同的方法可以检测到不同的射击边界。然后,我们着眼于结合三种镜头边界检测方法以产生一个输出结果,以及这给我们的系统带来的准确性和性能优势。每种方法都从使用三种非连接方法的静态阈值更改为使用一种连接方法的三个动态阈值的方法。在最后的总结中,我们展望了这项工作的未来方向。

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