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Non-accidental properties underlie human categorization of complex natural scenes

机译:非偶然属性是人类对复杂自然场景的分类基础

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摘要

Humans can categorize complex natural scenes quickly and accurately. Which scene properties enable us to do this with such apparent ease? We extracted structural properties of contours (orientation, length, curvature) and contour junctions (types and angles) from line drawings of natural scenes. All of these properties contain information about scene category that can be exploited computationally. But, when comparing error patterns from computational scene categorization with those from a six-alternative forced-choice scene categorization experiment, we found that only junctions and curvature made significant contributions to human behavior. To further test the critical role of these properties we perturbed junctions in line drawings by randomly shifting contours. As predicted, we found a significant decrease in human categorization accuracy. We conclude that scene categorization by humans relies on curvature as well as the same non-accidental junction properties used for object recognition. These properties correspond to the visual features represented in area V2.
机译:人类可以快速,准确地对复杂的自然场景进行分类。哪些场景属性使我们能够如此轻松地执行此操作?我们从自然场景的线条图中提取了轮廓(方向,长度,曲率)和轮廓交点(类型和角度)的结构属性。所有这些属性都包含有关场景类别的信息,可以通过计算利用这些信息。但是,当将来自计算场景分类的错误模式与六选择强制选择场景分类实验的错误模式进行比较时,我们发现只有路口和曲率对人类行为做出了重大贡献。为了进一步测试这些属性的关键作用,我们通过随机移动轮廓来扰乱线图中的连接点。如预期的那样,我们发现人类分类准确性显着下降。我们得出的结论是,人类对场景的分类依赖于曲率以及用于对象识别的非偶然结点属性。这些属性对应于区域V2中表示的视觉特征。

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