Dataset Information

The Recognition of Solid Object Shape: The Importance of Inhomogeneity.

ABSTRACT: A single experiment evaluated the haptic-visual cross-modal matching of solid object shape. One set of randomly shaped artificial objects was used (sinusoidally modulated spheres, SMS) as well as two sets of naturally shaped objects (bell peppers, Capsicum annuum and sweet potatoes, Ipomoea batatas). A total of 66 adults participated in the study. The participants' task was to haptically explore a single object on any particular trial and subsequently indicate which of 12 simultaneously visible objects possessed the same shape. The participants' performance for the natural objects was 60.9 and 78.7 percent correct for the bell peppers and sweet potatoes, respectively. The analogous performance for the SMS objects, while better than chance, was far worse (18.6 percent correct). All of these types of stimulus objects possess a rich geometrical structure (e.g., they all possess multiple elliptic, hyperbolic, and parabolic surface regions). Nevertheless, these three types of stimulus objects are perceived differently: Individual members of sweet potatoes and bell peppers are largely identifiable to human participants, while the individual SMS objects are not. Analyses of differential geometry indicate that these natural objects (e.g., bell peppers and sweet potatoes) possess heterogeneous spatial configurations of distinctly curved surface regions, and this heterogeneity is lacking in SMS objects. The current results therefore suggest that increases in surface structure heterogeneity facilitate human object recognition.

SUBMITTER: Norman JF

PROVIDER: S-EPMC6693026 | biostudies-other | 2019 Jul-Aug

REPOSITORIES: biostudies-other

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The Recognition of Solid Object Shape: The Importance of Inhomogeneity.

Norman J Farley JF Wheeler Sydney P SP Pedersen Lauren E LE Shain Lindsey M LM Kinnard Jonathan D JD Lenoir Joel J

i-Perception 20190701 4

A single experiment evaluated the haptic-visual cross-modal matching of solid object shape. One set of randomly shaped artificial objects was used (sinusoidally modulated spheres, SMS) as well as two sets of naturally shaped objects (bell peppers, <i>Capsicum annuum</i> and sweet potatoes, <i>Ipomoea batatas</i>). A total of 66 adults participated in the study. The participants' task was to haptically explore a single object on any particular trial and subsequently indicate which of 12 simultane ...[more]

PMID: 31448073

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Project description:It is debated whether the representation of objects in inferior temporal (IT) cortex is distributed over activities of many neurons or there are restricted islands of neurons responsive to a specific set of objects. There are lines of evidence demonstrating that fusiform face area (FFA-in human) processes information related to specialized object recognition (here we say within category object recognition such as face identification). Physiological studies have also discovered several patches in monkey ventral temporal lobe that are responsible for facial processing. Neuronal recording from these patches shows that neurons are highly selective for face images whereas for other objects we do not see such selectivity in IT. However, it is also well-supported that objects are encoded through distributed patterns of neural activities that are distinctive for each object category. It seems that visual cortex utilize different mechanisms for between category object recognition (e.g., face vs. non-face objects) vs. within category object recognition (e.g., two different faces). In this study, we address this question with computational simulations. We use two biologically inspired object recognition models and define two experiments which address these issues. The models have a hierarchical structure of several processing layers that simply simulate visual processing from V1 to aIT. We show, through computational modeling, that the difference between these two mechanisms of recognition can underlie the visual feature and extraction mechanism. It is argued that in order to perform generic and specialized object recognition, visual cortex must separate the mechanisms involved in within category from between categories object recognition. High recognition performance in within category object recognition can be guaranteed when class-specific features with intermediate size and complexity are extracted. However, generic object recognition requires a distributed universal dictionary of visual features in which the size of features does not have significant difference.

Dataset Information

The Recognition of Solid Object Shape: The Importance of Inhomogeneity.

Publications

The Recognition of Solid Object Shape: The Importance of Inhomogeneity.

Similar Datasets

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