MULTIPLE REPRESENTATIONS OF OBJECT SHAPE

描述（申请人摘要）：拟议的研究将调查 形状的表示，使我们能够识别物体在多个 抽象的层次。 我假设一个主要的代表， 对一个物体的各部分及其 相互关系-提供抽象的和相对不变的信息 这对于确定对象的一般类别（例如汽车）是有用的， 一个次要的表现形式-这是一个更敏感的观点（和 也许是基于视图的）度量丰富的表示-为 确定对象的特定标识（例如，“我的”汽车）。 拟议 研究将有助于越来越多的发现， 物体形状的多重综合表示概念 识别. 此外，拟议的研究将引入一个新的 实验方法来识别这些主要和次要的 表示。 提出的研究引入了一个新的框架，研究对象 在多个抽象层次上进行识别。 我们识别 多个抽象层次上的对象是非常重要的： 把物体看作是一般类别的成员，但不加以区分 个别情况肯定是不适应的;认识到 然而，一些例子没有意识到，不同的例子可能 属于一个共同的阶级也同样不适应。 尽管有 我们在多个层次上识别物体的能力的重要性 抽象，这种能力目前也不会被理解， 经验上或理论上。 拟议实验的结果将 有助于我们理解这一重要的能力， 对人类物体识别理论的重要限制。

DESCRIPTION (Applicant's Abstract): The proposed research will investigate the representations of shape that permit us to recognize objects at multiple levels of abstraction. I hypothesize that a primary representation-which is a categorical description of an object's parts and their interrelations-provides abstract and relatively view-invariant information that is useful for determining an object's general class (e.g. a car) and that a secondary representation-which is a more viewpoint-sensitive (and perhaps view-based) metrically-rich representation-provides a basis for determining an object s specific identify (e.g. "my" car). The proposed research will contribute to the growing body of findings supporting the notion of multiple, integrated representation of shape for object recognition. Moreover, the proposed research will introduce a new experimental method for identifying these primary and secondary representations. The proposed research introduces a new framework for studying object recognition at multiple levels of abstraction. Our ability to recognize objects at multiple levels of abstraction is centrally important: recognizing objects as members of a general class but not distinguishing individual instances would be decidedly maladaptive; and recognizing instances out failing to appreciate that different instances may nonetheless belong to a common class would be equally maladaptive. In spite of the importance of our capacity to recognize objects at multiple levels of abstraction, this capacity is currently not will understood, either empirically or theoretically. The results of the proposed experiments will contribute to our understanding of this important capacity, and place important constraints on theories of human object recognition.