Natural Object Categorization
Natural Object Categorization
复制标题
自然物体分类
DOI：
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发表时间：
1987
期刊：
影响因子：
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通讯作者：
A. Bobick
中科院分区：
文献类型：
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作者：
A. Bobick
翻译后摘要：本论文讨论的问题，自然对象的分类。为了提供一个分类的标准，我们建议分类的目的是支持从观察到的属性推断对象的未观察到的属性。因为在任意的世界中不可能构造出这样一组范畴，所以我们把自然模式原理作为关于世界结构的一个主张。我们首先定义一个评估函数，衡量一组类别如何支持观察者的推理目标。属性不确定性和类别不确定性的熵度量通过反映观察者目标的自由参数相结合。自然分类是那些相对于这个自由参数是稳定的。接下来，我们开发了一个利用分类评价函数恢复自然类别的分类范式。统计假设生成算法被证明是一个有效的分类过程。最后，提出了一种方法，用于评估的功能恢复自然类别的效用。该方法还提供了一种机制，用于确定哪些特征受到多模态世界中存在的不同过程的约束。
Abstract : This thesis addresses the problem of categorizing natural objects. To provide a criteria for categorization we propose that the purpose of a categorization is to support the inference of unobserved properties of objects from the observed properties. Because no such set of categories can be constructed in an arbitrary world, we present the Principle of Natural Modes as a claim about the structure of the world. We first define an evaluation function that measures how well a set of categories supports the inference goals of the observer. Entropy measures for property uncertainty and category uncertainty are combined through a free parameter that reflects the goals of the observer. Natural categorizations are shown to be those that are stable with respect to this free parameter. We next develop a categorization paradigm that utilizes the categorization evaluation function in recovering natural categories. A statistical hypothesis generation algorithm is presented that is shown to be an effective categorization procedure. Finally, a method is presented for evaluating the utility of features in recovering natural categories. This method also provides a mechanism for determining which features are constrained by the different processes present in a multiple modal world.