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On the space-time statistics of motion pictures
Journal of the Optical Society of America A ( IF 1.9 ) Pub Date : 2021-06-07 , DOI: 10.1364/josaa.413772 Dae Yeol Lee , Hyunsuk Ko , Jongho Kim , Alan C. Bovik
Journal of the Optical Society of America A ( IF 1.9 ) Pub Date : 2021-06-07 , DOI: 10.1364/josaa.413772 Dae Yeol Lee , Hyunsuk Ko , Jongho Kim , Alan C. Bovik
It is well known that natural images possess statistical regularities that can be captured by bandpass decomposition and divisive normalization processes that approximate early neural processing in the human visual system. We expand on these studies and present new findings on the properties of space-time natural statistics that are inherent in motion pictures. Our model relies on the concept of temporal bandpass (e.g., lag) filtering in lateral geniculate nucleus (LGN) and area V1, which is similar to smoothed frame differencing of video frames. Specifically, we model the statistics of the differences between adjacent or neighboring video frames that have been slightly spatially displaced relative to one another. We find that when these space-time differences are further subjected to locally pooled divisive normalization, statistical regularities (or lack thereof) arise that depend on the local motion trajectory. We find that bandpass and divisively normalized frame differences that are displaced along the motion direction exhibit stronger statistical regularities than for other displacements. Conversely, the direction-dependent regularities of displaced frame differences can be used to estimate the image motion (optical flow) by finding the space-time displacement paths that best preserve statistical regularity.
中文翻译:
论电影的时空统计
众所周知,自然图像具有统计规律,可以通过带通分解和分裂归一化过程来捕捉,这些过程近似于人类视觉系统中的早期神经处理。我们扩展了这些研究,并提出了关于电影中固有的时空自然统计特性的新发现。我们的模型依赖于外侧膝状体核 (LGN) 和区域 V1 中的时间带通(例如,滞后)滤波的概念,这类似于视频帧的平滑帧差分。具体来说,我们对相邻或相邻视频帧之间的差异统计数据进行建模,这些视频帧相对于彼此在空间上发生了轻微的位移。我们发现,当这些时空差异进一步受到局部汇集的分裂归一化时,出现依赖于局部运动轨迹的统计规律(或缺乏规律)。我们发现沿运动方向位移的带通和除法归一化帧差异比其他位移表现出更强的统计规律。相反,位移帧差异的方向相关规律可用于通过找到最能保持统计规律的时空位移路径来估计图像运动(光流)。
更新日期:2021-07-02
中文翻译:
论电影的时空统计
众所周知,自然图像具有统计规律,可以通过带通分解和分裂归一化过程来捕捉,这些过程近似于人类视觉系统中的早期神经处理。我们扩展了这些研究,并提出了关于电影中固有的时空自然统计特性的新发现。我们的模型依赖于外侧膝状体核 (LGN) 和区域 V1 中的时间带通(例如,滞后)滤波的概念,这类似于视频帧的平滑帧差分。具体来说,我们对相邻或相邻视频帧之间的差异统计数据进行建模,这些视频帧相对于彼此在空间上发生了轻微的位移。我们发现,当这些时空差异进一步受到局部汇集的分裂归一化时,出现依赖于局部运动轨迹的统计规律(或缺乏规律)。我们发现沿运动方向位移的带通和除法归一化帧差异比其他位移表现出更强的统计规律。相反,位移帧差异的方向相关规律可用于通过找到最能保持统计规律的时空位移路径来估计图像运动(光流)。