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光测几何线索与感知表面阴影

Photogeometric Cues to Perceived Surface Shading.

机构信息

School of Psychology, University of Sydney, 320 Griffith Taylor Building (A19), NSW 2006, Australia.

School of Psychology, University of Sydney, 320 Griffith Taylor Building (A19), NSW 2006, Australia.

出版信息

Curr Biol. 2019 Jan 21;29(2):306-311.e3. doi: 10.1016/j.cub.2018.11.041. Epub 2019 Jan 3.

DOI:10.1016/j.cub.2018.11.041
PMID:30612905
Abstract

The human visual system is remarkably adept at extracting the three-dimensional (3D) shape of surfaces from images of smoothly shaded surfaces (shape from shading). Most research into this remarkable perceptual ability has focused on understanding how the visual system derives a specific representation of 3D shape when it is known (or assumed) that shading and self-occluding contours are the sole causes of image structure [1-11]. But there is an even more fundamental problem that must be solved before any such analysis can take place: how does the visual system determine when it's viewing a shaded surface? Here, we present theoretical analyses showing that there is statistically reliable information generated along the bounding contours of smoothly curved surfaces that the visual system uses to identify surface shading. This information can be captured by two photogeometric constraints that link the shape of bounding contours to the distributions of shading intensity along the contours: one that links shading intensity to the local orientations along bounding contours and a second that links shading intensity to bounding contour curvature. We show that these constraints predict the perception of shading for surfaces with smooth self-occluding contours and a widely studied class of bounding contours (planar cuts). The results provide new insights into the information that the visual system exploits to distinguish surface shading from other sources of image structure and offer a coherent explanation of the influence of bounding contours on the perception of surface shading and 3D shape.

摘要

人类视觉系统非常擅长从平滑阴影表面的图像中提取表面的三维(3D)形状(形状从阴影中得出)。大多数关于这种非凡感知能力的研究都集中在理解视觉系统如何在已知(或假设)阴影和自遮挡轮廓是图像结构唯一原因的情况下得出特定的 3D 形状表示[1-11]。但是,在进行任何此类分析之前,必须先解决一个更基本的问题:视觉系统如何确定它正在观察阴影表面?在这里,我们提出了理论分析,表明在平滑弯曲表面的边界轮廓上会产生可统计可靠的信息,视觉系统可以利用这些信息来识别表面阴影。这些信息可以通过两个光几何约束来捕获,这两个约束将边界轮廓的形状与轮廓上的阴影强度分布联系起来:一个将阴影强度与边界轮廓上的局部方向联系起来,另一个将阴影强度与边界轮廓曲率联系起来。我们表明,这些约束可以预测具有平滑自遮挡轮廓和广泛研究的边界轮廓类(平面切口)的表面的阴影感知。这些结果提供了有关视觉系统利用区分表面阴影与图像结构其他来源的信息的新见解,并为边界轮廓对表面阴影和 3D 形状感知的影响提供了一致的解释。

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