Motion-Compensated Frame Interpolation (MCFI) is one of the common temporal-domain tamper operations, and it is used to produce faked video frames for improving the visual qualities of video sequences. The instability of temporal symmetry results in many incorrect Motion Vectors (MVs) for Bidirectional Motion Estimation (BME) in MCFI. The existing Motion Vector Smoothing (MVS) works often oversmooth or revise correct MVs as wrong ones. To overcome this problem, we propose a Cellular Automata-based MVS (CA-MVS) algorithm to smooth the Motion Vector Field (MVF) output by BME. In our work, a cellular automaton is constructed to deduce MV outliers according to a defined local evolution rule. By performing CA-based evolution in a loop iteration, we gradually expose MV outliers and reduce incorrect MVs resulting from oversmoothing as many as possible. Experimental results show the proposed algorithm can improve the accuracy of BME and provide better objective and subjective interpolation qualities when compared with the traditional MVS algorithms.

中文翻译：

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基于细胞自动机的运动矢量平滑的运动补偿帧插值

运动补偿帧插值（MCFI）是常见的时域篡改操作之一，用于生成伪造的视频帧，以提高视频序列的视觉质量。时间对称性的不稳定性导致MCFI中的双向运动估计（BME）出现许多错误的运动矢量（MV）。现有的运动矢量平滑（MVS）通常会使平滑的MV变平滑或将其修改为错误的MV。为克服此问题，我们提出了一种基于细胞自动机的MVS（CA-MVS）算法，以平滑BME输出的运动矢量场（MVF）。在我们的工作中，根据定义的局部进化规则，构造了一个细胞自动机来推断MV离群值。通过在循环迭代中执行基于CA的演化，我们逐渐暴露了MV离群值，并尽可能减少了因过度平滑而导致的不正确MV。