Perceptual Organization of Two Dimensional Patterns

项目摘要/摘要 视觉系统必须(通过一生的进化和学习)与生物体的自然任务相匹配 表演是为了生存和繁殖。因此，从根本上分析视觉系统是非常重要的 与自然任务以及与执行这些任务相关的自然刺激的统计特性有关。在我们的实验室 我们称之为“自然系统分析”。这一视觉科学的新方法由几个步骤组成：(1) 确定自然任务，(2)测量与这些任务相关的自然场景统计数据，(3)确定如何 在给定适当的生物限制的情况下，最好使用这些统计数据来执行任务，以及(4)使用第一个 制定原则性假设的三个步骤，这些假设在行为或生理上得到检验和提炼 实验。使用一套独特的测量设备、计算工具和心理物理 在我们实验室开发的范例中，我们建议(在自然系统的框架内) 分析)视觉任务的四个基本且相互关联的类别：(1)图像内插，其中目标是 估计由于遮挡表面、正常视锥采样或异常视锥而丢失的视网膜图像信息 损失，(2)估计对象(表面)边界位置以及边界的哪一侧在前景中 (更接近)，(3)散焦估计，其中的目标是估计图像散焦的大小和符号 视网膜图像的局部区域，以及(4)视觉外围的对比度和清晰度估计，其中 神经节细胞对视网膜图像进行严重过滤和下采样。任务(1)和任务(2)的总体目标是 要构建视觉系统如何识别遮挡区域并在其后面插入的完整图像 在自然条件下。处理任务(3)和(4)的总体目标是理解视觉 系统估计中心凹和周边的离焦和对比度，这与前两个任务相关。 许多拟议的研究将是第一次准确地描述自然环境中的统计约束 图像是视觉系统准确执行这些任务的能力的基础。许多拟议的研究 也将是第一个使用自然刺激来衡量这些基本任务的表现的人。有前途的飞行员 在许多拟议的研究中都获得了数据。

Project Summary/Abstract Visual systems must be matched (via evolution and learning over the lifespan) to the natural tasks organisms perform to survive and reproduce. Thus, it is of fundamental importance to analyze visual systems with respect to natural tasks and to the statistical properties of natural stimuli relevant to performing those tasks. In our lab we call this "natural systems analysis." This novel approach to vision science is composed of several steps: (1) identify natural tasks, (2) measure the natural scene statistics relevant for those tasks, (3) determine how to optimally use those statistics to perform the tasks, given appropriate biological constraints, and (4) use the first three steps to formulate principled hypotheses which are tested and refined in behavioral or physiological experiments. Using a unique suite of measurement devices, computational tools, and psychophysical paradigms developed in our laboratory, we propose to tackle (within the framework of natural systems analysis) four fundamental and interrelated classes of visual tasks: (1) image interpolation, where the goal is to estimate missing retinal image information due to occluding surfaces, normal cone sampling, or abnormal cone loss, (2) estimation of object (surface) boundary locations and which side of the boundary is in the foreground (nearer), (3) defocus estimation, where the goal is to estimate the magnitude and sign of image defocus in local regions of the retinal image, and (4) contrast and sharpness estimation in the visual periphery, where the ganglion cells severely filter and down sample the retinal image. The overall aim of tackling tasks (1) and (2) is to build an integrated picture of how the visual system identifies occlusion regions and interpolates behind them under natural conditions. The overall aim of tackling tasks (3) and (4) is to understand how the visual system estimates defocus and contrast in the fovea and periphery, which are relevant to the first two tasks. Many of the proposed studies will be the first to precisely characterize the statistical constraints in natural images underlying the visual system's ability to perform these tasks accurately. Many of the proposed studies will also be the first to measure performance in these fundamental tasks using natural stimuli. Promising pilot data has been obtained in many of the proposed studies.