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A robust and low-complexity video fingerprint for multimedia security

机译:强大且低复杂度的视频指纹,可确保多媒体安全

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Multimedia security means protecting multimedia information and information systems from unauthorized access, use, disclosure, disruption, modification, inspection, recording and destruction. The “Video Copy Detection” system is based on detecting video copies from a video sample to avoid copyright violations. Video fingerprinting is one of methods for video copy detection, including steps of video fingerprinting extraction and matching. Unlike previous video fingerprinting methods, a novel efficient and robust video fingerprint based on region of interest (ROI) and clustering is presented in this paper. In video fingerprinting extraction step, ROI is extended as basic unit for extracting video fingerprints. Features of Freak (fast retina keypoint) extracted from ROIs and clustered by spectral clustering later will be used as video fingerprints. In the matching step, we extend the method based on the classical cosine similarity with a significant change to measure the distance between video fingerprints. Results show that the proposed video fingerprinting exceeds several representative methods on its low-complexity and its robust on perceived similar alterations especially on text insertion, logo insertion, cropping, padding, frame dropping and fps changing et al.
机译:多媒体安全性是指保护多媒体信息和信息系统免受未经授权的访问,使用,披露,破坏,修改,检查,记录和破坏。 “视频拷贝检测”系统基于检测视频样本中的视频拷贝,以避免侵犯版权。视频指纹识别是视频拷贝检测的方法之一,包括视频指纹提取和匹配的步骤。与以前的视频指纹方法不同,本文提出了一种基于感兴趣区域(ROI)和聚类的新颖高效且鲁棒的视频指纹。在视频指纹提取步骤中,ROI被扩展为提取视频指纹的基本单元。从ROI中提取的“怪胎”(快速视网膜关键点)特征,随后通过光谱聚类进行聚类,将用作视频指纹。在匹配步骤中,我们将基于经典余弦相似性的方法进行了扩展,并进行了重大更改以测量视频指纹之间的距离。结果表明,所提出的视频指纹识别技术在复杂度低,对感知的相似变化(尤其是文本插入,徽标插入,裁剪,填充,丢帧和fps更改等)的鲁棒性方面超过了几种代表性方法。

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