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首页> 外文期刊>International journal of digital crime and forensics >Performance evaluation and scheme selection of shot boundary detection and keyframe extraction in content-based video retrieval
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Performance evaluation and scheme selection of shot boundary detection and keyframe extraction in content-based video retrieval

机译:基于内容的视频检索中镜头边界检测和关键帧提取的性能评估和方案选择

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摘要

The advancement of multimedia technology has contributed to a large number of videos, so it is important to know how to retrieve information from video, especially for crime prevention and forensics. For the convenience of retrieving video data, content-based video retrieval (CBVR) has got great publicity. Aiming at improving the retrieval performance, we focus on the two key technologies: Shot boundary detection and keyframe extraction. After being compared with pixel analysis and chisquare histogram, histogram-based method is chosen in this paper. Then we combine it with adaptive threshold method and use HSV color space to get the histogram. For keyframe extraction, four methods are analyzed and four evaluation criteria are summarized, both objective and subjective, so the opinion is finally given that different types of keyframe extraction methods can be used for varied types of videos. Then the retrieval can be based on keyframes, simplifying the process of video investigation, and helping criminal investigation personnel to improve work efficiency.
机译:多媒体技术的发展为大量视频做出了贡献,因此了解如何从视频中检索信息非常重要,特别是对于预防犯罪和法医学。为了方便检索视频数据,基于内容的视频检索(CBVR)得到了广泛的宣传。为了提高检索性能,我们专注于两个关键技术:镜头边界检测和关键帧提取。在与像素分析和卡方直方图进行比较之后,本文选择了基于直方图的方法。然后将其与自适应阈值方法相结合,并使用HSV颜色空间来获取直方图。对于关键帧提取,分析了四种方法,总结了客观和主观的四种评估标准,因此最终认为不同类型的关键帧提取方法可用于各种类型的视频。然后可以基于关键帧进行检索,从而简化了视频调查的过程,并帮助刑事侦查人员提高工作效率。

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