Object Perception Mechanisms for Resolving Ambiguity

解决歧义的对象感知机制

• 批准号: 6710204
• 负责人: DANIEL J KERSTEN
• 金额: $ 34万
• 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/6710204
• 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）：尽管自然图像非常复杂且客观模糊，但人类仍能快速可靠地感知物体的形状。由于投影的影响以及遮挡、背景杂乱、照明和视点的巨大变化，物体的图像特征是不明确的。日常视觉的成功意味着尚未被理解的神经机制，它将模糊或“嘈杂”的局部特征组织成物体和表面。我们过去在视觉感知贝叶斯理论方面的工作表明，如何通过先验对象知识与图像特征的概率整合来解决模糊性。我们建议扩展这项工作，以开发和测试解决对象感知模糊性的功能和机制的模型。 我们提出了四个系列的实验，使用心理物理学、计算和神经成像方法来研究人类视觉系统如何确定给定遮挡的物体形状，根据模糊线索构建表面表示，估计物体深度的变化和现实背景杂乱中的片段形状。