Acquisition of visual shape primitives.
Acquisition of visual shape primitives.
复制标题
获取视觉形状基元。
DOI：
10.1016/s0042-6989(02)00130-x
复制
发表时间：
2002
期刊：
影响因子：
1.8
通讯作者：
vonderMalsburg,Christoph
中科院分区：
文献类型：
--
作者：
Shams,Ladan;vonderMalsburg,Christoph
形状基元长期以来一直被提议作为视觉系统中对象模型的组件，并解释了大量的行为发现。虽然人们投入了大量的精力来研究场景中这些部分的检测，但尚未进行模拟获取这些表示的研究。我们提出了一个模型，该模型表明如何通过自组织方式的经验来学习形状基元。该模型提供了第一个成功的形状基元的无监督学习，形状基元与对象部件一样复杂，并且可以作为各种对象的中间表示。该算法使用合成的灰度对象，每个对象由多个部分（基元或其他）组成，并且形状基元是多个对象之间部分匹配的结果。我们的算法不使用有关要学习的模式的任何属性的任何先验知识；这些视觉模式在各种物体中的重现是它们作为新特征出现的唯一基础。
Shape primitives have long been proposed as components for object models in the visual system, and account for a considerable body of behavioral findings. While a large amount of effort has been devoted to the study of detection of these parts in the scenes, no research has been undertaken simulating the acquisition of these representations. We present a model which suggests how the shape primitives may be learned by experience in a self-organized fashion. This model offers the first successful unsupervised learning of shape primitives which are as complex as object parts and can serve as intermediate representations for various objects. The algorithm uses synthetic gray-level objects, each composed of several parts (primitives or else), and shape primitives emerge as a result of partial matches between several objects. Our algorithm does not use any a priori knowledge about any attributes of the patterns to be learned; and the recurrence of these visual patterns in various objects is the only basis for their emergence as new features.