STEREOSCOPIC SURFACE PERCEPTION

视觉空间感知的问题是从到达眼睛的光模式中恢复场景中对象的位置、形状、大小和方向。视觉系统使用两个视网膜图像之间的差异来收集关于场景的3D布局的信息。但是，曲面产生的水平差异是斜度和曲率的模糊指示器。例如，这种差异受倾斜度和相对于头部的位置的影响。因此，视觉系统必须“校正”和“归一化”水平差异，以确定表面倾斜和曲率。可以使用许多信号，包括垂直差异、感知的眼睛位置和非立体透视信号，它们是否实际使用，如果是，在什么条件下使用？心理物理实验将对不同轴线的倾斜感知进行；垂直视差、眼睛位置和透视信号将被操纵以确定它们的贡献。还将进行曲率感知的实验。存在许多立体现象，其中感知的倾斜度或曲率不能直接从视差中预测。这些错觉(例如，深度对比度，Craik-O‘Brien)被认为是视觉系统不能准确地解释视差并且不能从立体视觉中获得场景的准确3D表示的证据。它们实际上是可以被理解的。通过分析可用信号及其统计可靠性。将进行实验来检验这一解释的正确性。倾斜和曲率感知可以通过对每个估计器分配不同权重的倾斜和曲率估计器的输出的线性组合来建模。权重随观看情况而相应改变。人们可以通过触觉反馈来影响体重。实验将确定哪些重量可以通过触觉反馈改变，以及这些改变如何在不同条件下推广。从结果中，人们将能够确定估计者独立的处理水平。实验结果将被用于改进倾斜和曲率估计的理论。更好地了解表面感知将有助于开发和评估各种生物工程应用中使用的显示器，如手术、车辆模拟器和其他虚拟现实应用的远程成像。更好的理解也将有助于治疗患者接受新眼镜或其他改变图像的光学干预时造成的空间扭曲。

The problem of visual space perception is the recovery of the location, shape, size, and orientation of objects in the scene from the light pattern reaching the eyes. The visual system uses disparities between the two retinal images to glean information about the 3D layout of the scene. However, the horizontal disparities created by a surface are an ambiguous indicator of slant and curvature. For example, such disparities are affected by slant as well as position relative to the head. Thus, the visual system must "correct" and "normalize" horizontal disparities in order to determine surface slant and curvature. Many signals could be used including vertical disparities, sensed eye position, and non-stereoscopic perspective signals Are they actually used and, if so, under what conditions? Psychophysical experiments will be conducted on slant perception with respect to various axes; vertical disparity, eye position, and perspective signals will be manipulated to determine their contributions. Experiments will also be conducted on curvature perception. There are many stereoscopic phenomena in which the perceived slant or curvature is not directly predictable from the disparities. These illusions (e.g., depth contrast, Craik-O'Brien) have been regarded as evidence that the visual system does not interpret disparity accurately and does not derive from stereopsis an accurate 3D representation of the scene. They can actually be understood. by analyzing the available signals and their statistical reliabilities. Experiments will be conducted to test this explanation's validity. Slant and curvature percepts can be modeled by linear combination of the outputs of slant and curvature estimators with different weights assigned to each estimator. The weights change appropriately with viewing situation. One can affect the weights through haptic feedback. Experiments will determine which weights are changeable via haptic feedback and how the changes generalize across conditions. From the results, one will be able to determine the level of processing at which the estimators are independent. The experimental results will be used to refine a theory of slant and curvature estimation. A better understanding of surface perception will aid development and assessment of displays used in various bioengineering applications such as remote imaging of surgery, vehicle simulators, and other virtual reality applications. A better understanding will also aid treatment of spatial distortions created when patients receive new spectacles or other optical interventions that alter image.