Visual Search and Detection in Natural Scenes

项目摘要/摘要 其主要目的是了解人类和非人类灵长类动物 在自然条件下定位和识别目标对象，这是一项普遍存在的基本视觉任务。 在自然条件下，物体的定位和识别是困难的，因为物体太多了 自然任务中不确定性(可变性)的维度：中背景场景的高度可变属性 其中可以嵌入目标对象，关于目标对象可能的2D(或3D)位置的不确定性 场景、目标对象的2D(或3D)方向的不确定性以及对比度的不确定性 目标对象的。这些不确定性的自然维度推动了视觉系统的设计(尽管 进化和学习)。因此，对不确定性影响的理论和实验分析是至关重要的。 为了理解视觉系统执行的神经计算，以及潜在的神经 电路。在初步研究中，我们在发展识别和识别理论方面取得了实质性进展 在开发相关的计算和神经生理学工具时，在自然条件下进行本地化 在人类身上进行相关的行为测量，并在 表现得像猴子一样。第一个目标将是严格测试一些假设，这些假设是 不同维度的目标和背景不确定性单独存在，并结合在一起，影响行为和神经 计算。第二个目标是对一个重要因素(部分掩蔽)进行测量和建模 这会影响自然背景下的检测和识别性能，但从来没有系统地 在简单或自然的背景下进行调查。第三个目标建立在前两个目标的基础上，并将是 指导开发和测试一种新的显性和隐蔽视觉搜索理论，该理论考虑了自然 场景统计，神经节细胞采样和RF大小随视网膜位置的变化，以及固有的变化 视网膜位置的位置不确定。这一理论包含了许多具体的模型，每个模型 对任意特定搜索刺激进行详细的定量和定性预测。隐蔽搜查和公开搜查 噪声和自然背景中的任务将用于区分模型。

Project Summary/Abstract The broad aim is to understand the mechanisms that underlie the ability of human and non-human primates to locate and identify target objects under natural conditions, a ubiquitous and fundamental visual task. Localization and identification of objects under natural conditions is difficult because there are so many dimensions of uncertainty (variability) in natural tasks: highly-variable properties of the background scenes in which the target object may be embedded, uncertainty about possible 2D (or 3D) location of the target object in the scene, uncertainty about the 2D (or 3D) orientation of the target object, and uncertainty about the contrast of the target object. These natural dimensions of uncertainty drove the design of the visual system (though evolution and learning). Thus, the theoretical and experimental analysis of the effects of uncertainty is critical for understanding the neural computations performed by the visual system, as well as the underlying neural circuits. In preliminary studies, we made substantial progress in developing the theory of identification and localization under natural conditions, in developing relevant computational and neurophysiological tools, in making relevant behavioral measurements in humans, and in making relevant physiological measurements in behaving monkeys. The first aim will be directed at rigorously testing a number of hypotheses about how various dimensions of target and background uncertainty singly, and in combination, affect behavior and neural computation. The second aim will be directed at measuring and modeling an important factor (partial masking) that affects detection and identification performance in natural backgrounds, but has never been systematically investigated in either simple or natural backgrounds. The third aim builds on the first two aims and will be directed a developing and testing a new theory of overt and covert visual search that takes into account natural scene statistics, variation in ganglion cell sampling and RF size with retinal location, and variation in intrinsic position uncertainty with retinal location. The theory encompasses many specific models that each makes detailed quantitative and qualitative predictions for arbitrary specific search stimuli. Covert and overt search tasks in noise and natural backgrounds will be used to discriminate between models.