Object Perception Mechanisms for Resolving Ambiguity

解决歧义的对象感知机制

• 批准号: 6989711
• 负责人: DANIEL J KERSTEN
• 金额: $ 35.19万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-12-01 至 2007-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6989711
• 关键词: clinical research; computational neuroscience; cues; functional magnetic resonance imaging; human subject; neural information processing; psychophysiology; visual depth perception; visual perception

DESCRIPTION (provided by applicant): Humans perceive the shapes of objects quickly and reliably despite the complexity and objective ambiguities of natural images. Image features for an object are ambiguous because of the effects of projection together with large variations in occlusion, background clutter, illumination, and viewpoint. The very success of everyday vision implies neural mechanisms, yet to be understood, that organize ambiguous or "noisy" local features into objects and surfaces. Our past work in Bayesian theories of visual perception has shown how ambiguity may be resolved through the probabilistic integration of prior object knowledge with image features. We propose to extend this work to develop and test models of the functions and mechanisms underlying the resolution of ambiguity in object perception. We propose four series of experiments that use psychophysical, computational, and neuroimaging methods to investigate how the human visual system determines object shape given occlusion, constructs surface representations from ambiguous cues, estimates changes in object depth and segments shape from realistic background clutter.

描述（由申请人提供）：尽管自然图像的复杂性和客观歧义，人类仍会迅速而可靠地感知物体的形状。物体的图像特征是模棱两可的，因为投影的影响以及遮挡，背景混乱，照明和观点的巨大变化。日常视觉的成功意味着神经机制尚未理解，它将模棱两可或“嘈杂”的局部特征组织到对象和表面中。我们过去在贝叶斯的视觉感知理论中的工作表明，通过将先前对象知识与图像特征的概率整合通过概率整合可以解决歧义。我们建议扩展这项工作，以开发和测试对象感知中歧义性歧义的功能和机制的模型。 我们建议使用心理物理，计算和神经影像学方法来研究人类视觉系统如何确定对象形状给定的遮挡，从模棱两可的提示中构造表面表示，估计物体深度的变化和从逼真的背景构造形状的变化。