Techniques for Detecting Video Shot Boundaries: A Review

S. Sharma, P. Malakar
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Abstract

Due to the Corona Virus Diseases (COVID-19) pandemic, education is completely dependent on digital platforms, so recent advances in technology have made a tremendous amount of video content available. Due to the huge amount of video content, content-based information retrieval has become more and more important. Video content retrieval, just like information retrieval, requires some pre-processing such as indexing, key frame selection, and, most importantly, accurate detection of video shots. This gives the way for video information to be stored in a manner that will allow easy access. Video processing plays a vital role in many large applications. The applications required to perform the various manipulations on video streams (as on frames or say shots). The high definition of video can take a lot of memory to store, so compression techniques are huge in demand. Also, object tracking or object identification is an area where much considerable research has taken place and it is in progress.
视频镜头边界检测技术综述
由于冠状病毒病(COVID-19)大流行,教育完全依赖于数字平台,因此最近的技术进步使大量视频内容成为可能。由于视频内容的庞大,基于内容的信息检索变得越来越重要。视频内容检索和信息检索一样,需要进行索引、关键帧选择等预处理,最重要的是对视频镜头进行准确检测。这为视频信息的存储提供了一种方便访问的方式。视频处理在许多大型应用中起着至关重要的作用。在视频流(如帧或镜头)上执行各种操作所需的应用程序。高清晰度的视频需要大量的内存来存储,因此对压缩技术的需求很大。此外,目标跟踪或目标识别是一个已经进行并正在进行大量研究的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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