视频指纹技术在视频检索、识别、安全等领域有着广泛的应用,提出一种基于压缩传感理论的鲁棒性视频指纹方法,该方法采用压缩传感的稀疏性和安全性对提取的视频关键帧进行采样,再对采样矩阵分块与分类,提取能量值大的一些子块构成新的特征矩阵。对特征矩阵使用奇异值分解,对较大奇异值量化编码生成指纹。同时,也提出了高效的两步匹配方案,通过粗精两步搜索对视频进行检索,提高了视频搜索速度,实验结果表明,能准确检测视频片段,对通常的视频处理具有较强鲁棒性,满足视频检索的实时要求。

Video fingerprinting techniques have many applications in video retrieval, identification, and security. A robust video fingerprinting based on compressed sensing is proposed. In video fingerprinting, video key clips extracted are sampled by using the sparse and safety of compressed sensing. Each matrix sample is made into blocks, from which several big energy blocks are made into a new feature matrix. The singular value is used as code for the fingerprinting by SVD from this new feature matrix. Furthermore, an efficient two step match algorithm is proposed to using a search and match approximation, which improves video searching speed. The experimental results show that the proposed video fingerprinting is accurate in identifying different video clips, robust against common video processing, and can retrieve videos in real-time.