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The automatic video shot detection and characterization for content-based video retrieval

机译:基于内容的视频检索自动视频拍摄和表征

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In this paper, firstly, several video shot detection technologies have been discussed. An edited video consists of two kinds of shot boundaries been known as straight cuts and optical cuts. Experimental results using a variety of videos are presented to demonstrate that moving window detection algorithm and 10-step difference histogram comparison algorithm are effective for detection of both kinds of shot cuts. After shot isolation, methods for shot characterization were investigated. We present a detailed discussion of key-frame extraction and review the visual features, particularly the color feature based on HSV model, of key-frames. Video retrieval methods based on key-frames have been presented at the end of this section. This paper also presents an integrated system solution for computer-assisted video parsing and content-based video retrieval. The application software package was programmed on Visual C++ development platform.
机译:本文首先,已经讨论了几种视频拍摄检测技术。编辑的视频由两种射击边界组成,被称为直切割和光学切割。提出了使用各种视频的实验结果来证明移动窗口检测算法和10步差直方图比较算法对于检测两种射击切割是有效的。拍摄隔离后,研究了拍摄表征的方法。我们介绍了关键帧提取的详细讨论,并查看了基于键帧的基于HSV模型的视觉功能,特别是彩色功能。基于键帧的视频检索方法已在本节末尾呈现。本文还提出了一种用于计算机辅助视频解析和基于内容的视频检索的集成系统解决方案。应用软件包在Visual C ++开发平台上编程。

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