Estimation and Discrimination of Motion and Depth in Natural Scenes

项目摘要/摘要 视觉研究的一个基本目标是了解视觉在自然条件下是如何工作的。视觉系统 与生物体为生存和繁殖所执行的关键任务相匹配。因此，从根本上说，它是 重要的是分析与这些任务相关的视觉系统以及符合以下条件的自然刺激的特性 与这些任务相关。我的实验室采用了以下方法。首先，我们测量与任务相关的统计数据 自然刺激的性质。下一步，考虑到生物限制，我们决定如何最佳地利用这些限制 属性来执行任务。然后，我们根据前两个步骤制定假设，并在 用自然刺激进行的行为实验。将我们的结果与经典文献联系起来，并确定 一般而言，我们的结果，我们也收集数据与人工刺激。使用一套独特的自然图像 数据库、计算工具和心理物理范例(其中许多已经开发或 在我们的实验室中得到完善)，我们建议研究几项与估计 自然场景中的深度和运动。目标1研究自然界中的最优和人类视差估计 立体图像。目的2研究自然图像电影中的最佳运动估计和人体运动估计。目标3 研究自然立体图像电影中的最佳和人体运动深度估计。许多人 拟议的研究将是第一次表征自然图像的统计特性，这些特性是 人类准确执行这些任务的能力。许多拟议中的研究也将是第一个衡量 人类在这些任务中使用自然刺激的表现。这些研究的结果不仅将是独特的新的 但新的原则性模型可以预测人类在自然条件下的表现和 指导未来对潜在机制的行为和神经生理学研究。令人鼓舞的初步结果 许多拟议的研究都取得了成果。 好了！

Project Summary/Abstract A fundamental goal of vision research is to understand how vision works in natural conditions. Vision systems are matched to the critical tasks that organisms perform to survive and reproduce. Thus, it is fundamentally important to analyze vision systems with respect to these tasks, and the properties of natural stimuli that are relevant to those tasks. My lab takes the following approach. First, we measure task-relevant statistical properties of natural stimuli. Next, given biological constraints, we determine how to optimally use those properties to perform the tasks. Then, we formulate hypotheses based on the first two steps and test them in behavioral experiments with natural stimuli. To connect our results with the classic literature and determine the generality of our results, we also collect data with artificial stimuli. Using a unique suite of natural image databases, computational tools, and psychophysical paradigms (many of which have been developed or refined in our laboratory), we propose to investigate several fundamental tasks relevant for the estimation of depth and motion in natural scenes. Aim 1 investigates optimal and human disparity estimation in natural stereo-images. Aim 2 investigates optimal and human motion estimation in natural image movies. Aim 3 investigates optimal and human motion-in-depth estimation in natural stereo-image movies. Many of the proposed studies will be the first to characterize the statistical properties of natural images that underlie the human ability to perform these tasks accurately. Many of the proposed studies will also be the first to measure human performance in these tasks using natural stimuli. The result of these studies will be not only unique new measurements, but new principled models that can predict human performance under natural conditions and guide future behavioral and neurophysiological studies of the underlying mechanisms. Encouraging preliminary results have been obtained for many of the proposed studies. !