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语境差异:理解单目图像内容如何与人类视觉皮层中的视差处理相互作用。

Disparity in Context: Understanding how monocular image content interacts with disparity processing in human visual cortex.

机构信息

Wu Tsai Neurosciences Institute, 290 Jane Stanford Way, Stanford, CA 94305.

Department of Electrical Engineering, David Packard Building, Stanford University, 350 Jane Stanford Way, Stanford, CA 94305.

出版信息

Neuroimage. 2021 Aug 15;237:118139. doi: 10.1016/j.neuroimage.2021.118139. Epub 2021 May 5.

Abstract

Horizontal disparities between the two eyes' retinal images are the primary cue for depth. Commonly used random ot tereograms (RDS) intentionally camouflage the disparity cue, breaking the correlations between monocular image structure and the depth map that are present in natural images. Because of the nonlinear nature of visual processing, it is unlikely that simple computational rules derived from RDS will be sufficient to explain binocular vision in natural environments. In order to understand the interplay between natural scene structure and disparity encoding, we used a depth-image-based-rendering technique and a library of natural 3D stereo pairs to synthesize two novel stereogram types in which monocular scene content was manipulated independent of scene depth information. The half-images of the novel stereograms comprised either random-dots or scrambled natural scenes, each with the same depth maps as the corresponding natural scene stereograms. Using these stereograms in a simultaneous Event-Related Potential and behavioral discrimination task, we identified multiple disparity-contingent encoding stages between 100 ~ 500 msec. The first disparity sensitive evoked potential was observed at ~100 msec after an earlier evoked potential (between ~50-100 msec) that was sensitive to the structure of the monocular half-images but blind to disparity. Starting at ~150 msec, disparity responses were stereogram-specific and predictive of perceptual depth. Complex features associated with natural scene content are thus at least partially coded prior to disparity information, but these features and possibly others associated with natural scene content interact with disparity information only after an intermediate, 2D scene-independent disparity processing stage.

摘要

双眼视网膜图像的水平视差是深度的主要线索。常用的随机点立体图(RDS)故意伪装视差线索,打破了自然图像中存在的单眼图像结构与深度图之间的相关性。由于视觉处理的非线性性质,从 RDS 中得出的简单计算规则不太可能足以解释自然环境中的双眼视觉。为了理解自然场景结构与视差编码之间的相互作用,我们使用了基于深度图像的渲染技术和自然 3D 立体对库,合成了两种新的立体图类型,其中独立于场景深度信息来操纵单眼场景内容。新立体图的半图像由随机点或混叠自然场景组成,每个图像都具有与相应自然场景立体图相同的深度图。使用这些立体图在同时进行的事件相关电位和行为辨别任务中,我们在 100 到 500 毫秒之间识别出多个依赖于视差的编码阶段。在对单眼半图像的结构敏感的早期诱发电位(在 50-100 毫秒之间)之后约 100 毫秒观察到第一个对视差敏感的诱发电位,但对视差不敏感。从大约 150 毫秒开始,视差响应是立体图特有的,并且可以预测感知深度。因此,与自然场景内容相关的复杂特征至少部分地在视差信息之前被编码,但这些特征和可能与自然场景内容相关的其他特征仅在中间的、2D 与场景无关的视差处理阶段之后与视差信息相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a35c/10786599/91f66e29f328/nihms-1950892-f0001.jpg

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