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Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer

机译:更精细级别的对象分类更多地依赖于更高的空间频率并且需要更长的时间

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摘要

The human visual system contains a hierarchical sequence of modules that take part in visual perception at different levels of abstraction, i.e., superordinate, basic, and subordinate levels. One important question is to identify the “entry” level at which the visual representation is commenced in the process of object recognition. For a long time, it was believed that the basic level had a temporal advantage over two others. This claim has been challenged recently. Here we used a series of psychophysics experiments, based on a rapid presentation paradigm, as well as two computational models, with bandpass filtered images of five object classes to study the processing order of the categorization levels. In these experiments, we investigated the type of visual information required for categorizing objects in each level by varying the spatial frequency bands of the input image. The results of our psychophysics experiments and computational models are consistent. They indicate that the different spatial frequency information had different effects on object categorization in each level. In the absence of high frequency information, subordinate and basic level categorization are performed less accurately, while the superordinate level is performed well. This means that low frequency information is sufficient for superordinate level, but not for the basic and subordinate levels. These finer levels rely more on high frequency information, which appears to take longer to be processed, leading to longer reaction times. Finally, to avoid the ceiling effect, we evaluated the robustness of the results by adding different amounts of noise to the input images and repeating the experiments. As expected, the categorization accuracy decreased and the reaction time increased significantly, but the trends were the same. This shows that our results are not due to a ceiling effect. The compatibility between our psychophysical and computational results suggests that the temporal advantage of the superordinate (resp. basic) level to basic (resp. subordinate) level is mainly due to the computational constraints (the visual system processes higher spatial frequencies more slowly, and categorization in finer levels depends more on these higher spatial frequencies).
机译:人的视觉系统包含模块的层次结构序列,这些模块以不同的抽象级别(即上级,基本和下级)参与视觉感知。一个重要的问题是确定在对象识别过程中视觉表示开始的“入口”级别。长期以来,人们认为基本级别在时间上比其他两个级别具有优势。该主张最近受到质疑。在这里,我们使用了一系列基于快速表示范例的心理物理学实验以及两个计算模型,并通过五个对象类别的带通滤波图像研究了分类级别的处理顺序。在这些实验中,我们研究了通过改变输入图像的空间频带对每个级别的对象进行分类所需的视觉信息类型。我们的心理物理学实验和计算模型的结果是一致的。他们指出,不同的空间频率信息对每个级别的对象分类都有不同的影响。在没有高频信息的情况下,下级和基本级别的分类执行得较不准确,而上级级别则执行得很好。这意味着低频信息对于上级而言已足够,但对于基础级和下级而言却不够。这些更精细的级别更多地依赖于高频信息,这似乎需要更长的时间来处理,从而导致更长的反应时间。最后,为了避免天花板效应,我们通过向输入图像添加不同量的噪声并重复实验来评估结果的鲁棒性。正如预期的那样,分类准确性下降,反应时间显着增加,但是趋势是相同的。这表明我们的结果并不是由于上限效应。我们的心理和计算结果之间的兼容性表明,上级(相对于基本)级别到基本(相对于从属级别)的时间优势主要是由于计算约束(视觉系统处理较高的空间频率更慢,并且进行分类)更细微的水平更多地取决于这些更高的空间频率。

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