Perception and Action: Ideal Observers and Actors

感知与行动：理想的观察者和行动者

• 批准号: 6930501
• 负责人: MICHAEL S LANDY
• 金额: $ 30.05万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-08-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6930501
• 关键词: behavior test; behavioral /social science research tag; clinical research; cues; form /pattern perception; human subject; mathematical model; motion perception; neural information processing; psychophysics; space perception; vision tests; visual depth perception; visual fields; visual perception; visual stimulus

DESCRIPTION (provided by applicant): Biological visual systems make use of many different sources of information ("cues") for visual judgments. For depth and shape estimation, for example, these include occlusion, texture, perspective, motion parallax, disparity, shading and contour. The combination of these cues is based on the relative reliabilities of the individual cues, but cannot occur until cues are promoted to a commensurate scale by filling in one or more needed parameters (e.g., the fixation distance and azimuth for depth and slant estimates). These parameters are also estimated using multiple cues (e.g., both retinal and oculomotor cues for the viewing geometry). We propose statistical decision theoretic models for ideal behavior in the visual estimation of scene properties and for movement planning. The ideal observer or actor must take into account measurement uncertainty, associated with different outcomes, and prior information about the current state of the world. We propose experiments intended to clarify how human observers promote and combine cues for vision and for the visual control of action. The experimental methods used are based on perturbation analysis which permits examination of a system that can potentially react to distortions and inconsistencies in the stimuli. The proposed research consists of three major tasks. (1) We will analyze observer behavior relative to predictions of ideal Bayesian decision makers confronted by the same levels of uncertainty in tasks of perceptual decision, reaching and grasping. (2) We will examine cue combination in the service of cue promotion, again with reference to ideal behavior. (3) We will continue our studies of spatial interpolation performance so as to better understand such aspects of the underlying model as the prior distribution, and the methods used by the observer to be statistically robust (which, in this context, is closely related to the scene segmentation problem).

描述（由申请人提供）：生物视觉系统利用许多不同的信息来源（“提示”）进行视觉判断。例如，例如，这些深度和形状估计包括遮挡，纹理，透视图，运动视差，差异，阴影和轮廓。这些提示的组合是基于单个提示的相对可靠性，但是直到通过填充一个或多个所需参数（例如，固定距离和倾斜度估算值）来促进提示将提示提升为相称的规模，才能发生。这些参数还使用多个提示（例如，视网膜和眼动物提示用于观察几何形状）估算。我们提出了统计决策理论模型，以实现场景属性和运动计划的视觉估计中的理想行为。理想的观察者或演员必须考虑到测量不确定性，与不同的结果以及有关世界状况的先前信息相关的。我们提出的实验旨在阐明人类观察者如何促进和结合视觉和视觉控制动作的线索。所使用的实验方法基于扰动分析，该分析允许检查可能对刺激中的扭曲和不一致的系统进行检查。拟议的研究包括三个主要任务。 （1）我们将分析观察者的行为相对于理想的贝叶斯决策者的预测，在感知决策，达到和掌握的任务中，面临着相同水平的不确定性。 （2）我们将再次参考理想行为来研究提示促进的提示组合。 （3）我们将继续对空间插值性能进行研究，以便更好地理解基本模型的此类方面，例如先前的分布，以及观察者使用的方法在统计上具有稳定性（在这种情况下，这与场景细分问题密切相关）。