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

Abstract

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).

The Effect of Spatial Frequency on the Visual Category Representation in the Macaque Inferior Temporal Cortex

“…The amount of information loss due to the HSF filtering is same as the LSF in face categorization at the mid-level; however, HSF filtering of the body stimuli at the mid-level of abstraction preserves the amount of information compared to intact stimuli. This observation supports the evidence that suggests a special neural mechanism for face representation in IT cortex 19 . The effect of SF filtering on face information is also compatible with psychophysical studies where middle frequency bands are more critical for face perception rather than LSF and HSF [38][39][40][41] .…”

Object categorization in visual periphery is modulated by delayed foveal noise

“…Note that the accuracy drop in our peripheral object categorization task with foveal delayed noise cannot be due to the foveal load, a phenomenon also known as tunnel vision (Ball, Beard, Roenker, Miller, & Griggs, 1988;Ikeda & Takeuchi, 1975;Ringer, Throneburg, Johnson, Kramer, & Loschky, 2016; L. J. Williams, 1985).…”

“…Albeit crowding and low visual acuity of the periphery are the main factors limiting peripheral object recognition at finer abstraction levels, the contribution of each factor needs to be more carefully investigated in future studies. One way to address this can be performing similar experiments to ours but using band-pass filtered natural (cluttered) images in different spatial frequencies (Ashtiani, Kheradpisheh, Masquelier, & Ganjtabesh, 2017).…”

Both a Gauge and a Filter: Cognitive Modulations of Pupil Size

“…In object perception, pupil dilation might decrease information about object or face identity in favor of type, mimicking the effects of disrupting high spatial frequency information in images (124–127). This could make it easier to represent a figure according to more abstract classes—such as whether an object is a car or an animal—rather than according to fine grain distinctions between different animals (136). Finally, large pupils could also aid in estimating the three dimensional configuration of a scene—that is, the distance between ourselves and some salient cue.…”