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Real time and non real time video shot boundary detection using dual tree complex wavelet transform

机译:使用双树复小波变换的实时和非实时视频镜头边界检测

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The innovation being done in multimedia streams from last few years necessitates the development of efficient and more effective methodologies for storing information related to video, audio, text etc. Accessing of content based video data requires segmentation of each video stream into its primary blocks. The video stream consists of a number of shots, each sequence of frames are represented using a single camera. Switching from one frame to another indicates the transition from a shot to the next one. Therefore, the detection of these transitions, known as scene change or shot boundary detection, is the first step in any video-analysis system. A number of proposed techniques for solving the problem of shot boundary detection exist, but the major challenges to them are their ineffectiveness and lack of dependability. The reliability of the scene change detection stage is a very significant requirement because it is the initial stage in any video retrieval system. Thus, its performance has a direct impact on the performance of all other stages. On the other hand, efficiency is also crucial due to the voluminous amounts of information found in video streams. In this paper, a new robust and efficient paradigm capable of detecting transitions in AVI videos is tested.
机译:最近几年在多媒体流中进行的创新需要开发一种有效且更有效的方法来存储与视频,音频,文本等有关的信息。基于内容的视频数据的访问需要将每个视频流分割成其主要块。视频流由许多镜头组成,每个帧序列使用单个摄像机表示。从一帧切换到另一帧表示从一张镜头过渡到下一幅。因此,这些过渡的检测(称为场景变化或镜头边界检测)是任何视频分析系统的第一步。存在许多解决镜头边界检测问题的提议技术,但是对它们的主要挑战是它们的无效性和缺乏可靠性。场景变化检测阶段的可靠性是非常重要的要求,因为它是任何视频检索系统的初始阶段。因此,它的性能直接影响所有其他阶段的性能。另一方面,由于在视频流中发现了大量信息,因此效率也至关重要。在本文中,测试了一种能够检测AVI视频中的过渡的强大而有效的新范例。

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