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Video Sequence Matching Based on the Invariance of Color Correlation

机译:基于颜色相关不变性的视频序列匹配

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摘要

Video sequence matching aims to locate a query video clip in a video database. It plays an important role in reducing storage redundancy and detecting video copies for copyright protection. In this paper, we propose an effective method for video sequence matching based on the invariance of color correlation. The proposed method first splits each key-frame into nonoverlapping blocks. For each block, we sort the red, green, and blue color components according to their average intensities, and use the percentage of the color correlation to generate a frame feature with a small size. Finally, the resulting video feature is made up of the consecutive frame features, which is demonstrated to be robust against most typical video content-preserving operations, including geometric distortion, blurring, noise contamination, contrast enhancement, and strong re-encoding. The experimental results show that the proposed method outperforms the existing methods in the literature, as well as the method based on the traditional color histogram. Furthermore, the time and space complexity of our algorithm are both satisfactory, which are very important for many real-time applications.
机译:视频序列匹配旨在在视频数据库中定位查询视频剪辑。它在减少存储冗余和检测视频副本以保护版权方面起着重要作用。在本文中,我们提出了一种基于颜色相关性不变性的有效视频序列匹配方法。所提出的方法首先将每个关键帧分割成不重叠的块。对于每个块,我们根据红色,绿色和蓝色分量的平均强度对其进行排序,并使用颜色相关性的百分比来生成较小尺寸的帧特征。最后,最终的视频特征由连续的帧特征组成,这被证明对大多数典型的视频内容保留操作具有鲁棒性,包括几何失真,模糊,噪声污染,对比度增强和强大的重新编码。实验结果表明,该方法优于文献中已有的方法和基于传统颜色直方图的方法。此外,我们算法的时间和空间复杂度都令人满意,这对于许多实时应用而言非常重要。

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