Perceptual straightening of natural videos
Perceptual straightening of natural videos
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DOI：
10.1038/s41593-019-0377-4
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发表时间：
2019-06-01
影响因子：
25
通讯作者：
Simoncelli, Eero P.
中科院分区：
文献类型：
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作者：
Henaff, Olivier J.;Goris, Robbe L. T.;Simoncelli, Eero P.
许多行为依赖于来自最近的视觉输入的预测，但这些输入的时间演变通常是复杂的，难以推断。我们建议视觉系统将这些输入转换为更直的时间轨迹。为了测试这个“时间拉直”的假设，我们开发了一种方法来估计曲率的内部轨迹从人类的感知判断。我们用它来测试三个不同的预测：在像素强度空间中高度弯曲的自然序列应该在感知上更直;相反，在强度域中笔直的人工序列应该在感知上更弯曲;最后，在强度域中笔直的自然序列应该相对较少弯曲。感知数据验证了所有三个预测，就像早期视觉系统的人口模型一样，提供了视觉系统专门纠正自然视频的证据，为依赖预测的任务提供了解决方案。
Many behaviors rely on predictions derived from recent visual input, but the temporal evolution of those inputs is generally complex and difficult to extrapolate. We propose that the visual system transforms these inputs to follow straighter temporal trajectories. To test this 'temporal straightening' hypothesis, we develop a methodology for estimating the curvature of an internal trajectory from human perceptual judgments. We use this to test three distinct predictions: natural sequences that are highly curved in the space of pixel intensities should be substantially straighter perceptually; in contrast, artificial sequences that are straight in the intensity domain should be more curved perceptually; finally, naturalistic sequences that are straight in the intensity domain should be relatively less curved. Perceptual data validate all three predictions, as do population models of the early visual system, providing evidence that the visual system specifically straightens natural videos, offering a solution for tasks that rely on prediction.