ID 原文 译文
22645 运动补偿帧率提升(MC-FRUC)是常见的视频时域篡改手段。 Motion-Compensated Frame Rate Up-Conversion (MC-FRUC) is one of the common temporal-domain tampering methods of video.
22646 现有方法依靠被动分析视频统计特征发现MC-FRUC 篡改，然而，视频统计特性的非平稳性影响了取证性能的稳定性。 The existing methods recognize MC-FRUC tampering by passively analyzing statistical characteristics of video; however, the non-stationarity in statistics of video affects the stability of forensics.
22647 该文提出一种主动混噪取证算法。 This paper proposes an active noise-mixed forensics algorithm.
22648 首先，利用伪随机序列生成高斯白噪声，加入原始视频序列。 First, white Gaussian noises are produced using a pseudorandom sequence, and these noises are added into the original video sequence.
22649 接着，由小波系数的绝对中位差预测各视频帧中混入高斯噪声的标准差。 Second, based on the median absolute deviation of wavelet coefficients, the standard deviation of mixed Gaussian noises in each video frame is estimated.
22650 最后，检测高斯噪声标准差的时域变化周期性，通过硬阈值判决，自动甄别 MC-FRUC 篡改。 Last, the periodicity of standard deviation varying in time domain is detected, and MC-FRUC tampering with a hard-thresholding operation is automatically identified.
22651 实验结果表明，针对不同的 MC-FRUC伪造方法，提出算法均表现出良好的取证性能，尤其是当采用去噪、压缩等操作后处理视频后，提出算法仍能确保较高的检测准确度。 Experimental results indicate that the proposed algorithm presents better performance of forensics for various MC-FRUC methods, and can still ensure high detection accuracy especially after videos are denoised or compressed.
22652 针对目前信号数据域直接位置估计方法对分布式信号源进行直接定位存在精度下降问题，该文提出分布式信源数据域直接位置估计方法。 The traditional Direct Position Determination (DPD) methods have localization accuracy decrease when locating distributed sources. DPD methods of the distributed source is proposed in this paper to overcome the shortcoming mentioned above.
22653 首先构建分布式信源直接位置估计模型，然后分别基于最大似然准则和特征结构分解思想给出分布式信源高精度直接位置估计的两种方法：分布源最大似然估计方法和广义子空间方法。 Firstly, a DPD model of the distributed source is constructed. Then two new DPD methods based on maximum likelihood criterion and multiple signal classification are proposed to locate the distributed source: Maximum Likelihood estimation DPD method of the Distributed source (DML-DPD) and Generalized Subspace DPD method (GS-DPD).
22654 最后通过多维搜索完成对于分布式信源的直接位置估计。 Finally, target position is estimated via multidimensional grid search.