PERCEPTUAL ORGANIZATION OF TWO DIMENSIONAL PATTERNS

二维图案的感知组织

• 批准号: 2711211
• 负责人: WILSON S GEISLER
• 金额: $ 13.69万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-06-01 至 2000-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2711211
• 关键词: behavioral /social science research tag; brightness discrimination; computational neuroscience; human subject; mathematical model; neural information processing; neurophysiology; psychophysics; vision; visual perception; visual stimulus

DESCRIPTION: An established researcher in the area of early vision proposes to use psychophysical and computational methods to study grouping, segregation, and contour integration in multi-element patterns. Specific aims include: 1) the measurement of pairwise trading relationships in grouping strength for symmetry (e.g. how does spatial proximity interact with symmetry in grouping tasks?) 2) comparison of filter vs. structure-based models of grouping and segregation 3) testing of different models of contour integration, 4) measurements of eccentricity effects in texture segregation, 5) modeling of the mechanisms of perceptual organization in perception of complex images. The bulk of the data will be collected with a three element display. The subject's task will be to determine if the center item groups more strongly with the left or right flanking item. In other tasks (e.g. section 4.2) Ss will identify the orientation of a texture patch. A model of grouping is proposed starting with filtering by simple cells as previously modeled by Albrecht and Geisler. A second, "transformational" matching stage allows for similar items to be grouped together. In a complex image, the plan is to have receptive field matching generate a first set of primitives that can be grouped. These groups are then subject to transformational mapping and higher-order groupings can be based on the results of that operation. Grouping is based on a variety of grouping rules (e.g. figure-ground grouping, associative grouping - a principle that holds that if A and B group and B and C group than A and C will group). The model asserts that grouping can be "multi-level" though it is admitted that "our current understanding of multiple-level grouping" is in a rather primitive state.

描述：早期视力领域的一位知名研究人员提出 使用心理物理学和计算方法来研究分组， 多元素图案中的分离和轮廓整合。 具体的 目标包括：1）衡量成对交易关系 对称性的分组强度（例如，空间邻近度如何相互作用 分组任务中是否具有对称性？）2）过滤器与过滤器的比较 基于结构的分组和隔离模型 3) 不同的测试 轮廓积分模型，4）偏心效应的测量 纹理分离，5）感知机制的建模 复杂图像感知的组织。 大部分数据将是 通过三元素显示收集。 主题的任务是 确定中心项目与左侧或右侧的分组是否更紧密 侧翼项目。 在其他任务中（例如第 4.2 节），Ss 将识别 纹理补丁的方向。 提出分组模型 通过简单单元进行过滤，如 Albrecht 之前建模的那样 盖斯勒。 第二个“转型”匹配阶段允许类似的 要分组在一起的项目。 在复杂的图像中，计划是 感受野匹配生成第一组基元，可以 分组。 然后对这些组进行转换映射并 高阶分组可以基于该操作的结果。 分组基于各种分组规则（例如图形-背景 分组、关联分组 - 该原则认为如果 A 和 B 组和B和C组比A和C组要多）。 该模型断言 分组可以是“多层次的”，尽管承认“我们目前的 对多级分组的理解还处于相当原始的状态。