Dataset Information

Skeletal descriptions of shape provide unique perceptual information for object recognition.

ABSTRACT: With seemingly little effort, humans can both identify an object across large changes in orientation and extend category membership to novel exemplars. Although researchers argue that object shape is crucial in these cases, there are open questions as to how shape is represented for object recognition. Here we tested whether the human visual system incorporates a three-dimensional skeletal descriptor of shape to determine an object's identity. Skeletal models not only provide a compact description of an object's global shape structure, but also provide a quantitative metric by which to compare the visual similarity between shapes. Our results showed that a model of skeletal similarity explained the greatest amount of variance in participants' object dissimilarity judgments when compared with other computational models of visual similarity (Experiment 1). Moreover, parametric changes to an object's skeleton led to proportional changes in perceived similarity, even when controlling for another model of structure (Experiment 2). Importantly, participants preferentially categorized objects by their skeletons across changes to local shape contours and non-accidental properties (Experiment 3). Our findings highlight the importance of skeletal structure in vision, not only as a shape descriptor, but also as a diagnostic cue of object identity.

SUBMITTER: Ayzenberg V

PROVIDER: S-EPMC6597715 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Skeletal descriptions of shape provide unique perceptual information for object recognition.

Ayzenberg Vladislav V Lourenco Stella F SF

Scientific reports 20190627 1

With seemingly little effort, humans can both identify an object across large changes in orientation and extend category membership to novel exemplars. Although researchers argue that object shape is crucial in these cases, there are open questions as to how shape is represented for object recognition. Here we tested whether the human visual system incorporates a three-dimensional skeletal descriptor of shape to determine an object's identity. Skeletal models not only provide a compact descripti ...[more]

PMID: 31249321

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Project description:Active echolocation allows blind individuals to explore their surroundings via self-generated sounds, similarly to dolphins and other echolocating animals. Echolocators emit sounds, such as finger snaps or mouth clicks, and parse the returning echoes for information about their surroundings, including the location, size, and material composition of objects. Because a crucial function of perceiving objects is to enable effective interaction with them, it is important to understand the degree to which three-dimensional shape information extracted from object echoes is useful in the context of other modalities such as haptics or vision. Here, we investigated the resolution of crossmodal transfer of object-level information between acoustic echoes and other senses. First, in a delayed match-to-sample task, blind expert echolocators and sighted control participants inspected common (everyday) and novel target objects using echolocation, then distinguished the target object from a distractor using only haptic information. For blind participants, discrimination accuracy was overall above chance and similar for both common and novel objects, whereas as a group, sighted participants performed above chance for the common, but not novel objects, suggesting that some coarse object information (a) is available to both expert blind and novice sighted echolocators, (b) transfers from auditory to haptic modalities, and (c) may be facilitated by prior object familiarity and/or material differences, particularly for novice echolocators. Next, to estimate an equivalent resolution in visual terms, we briefly presented blurred images of the novel stimuli to sighted participants (N = 22), who then performed the same haptic discrimination task. We found that visuo-haptic discrimination performance approximately matched echo-haptic discrimination for a Gaussian blur kernel σ of ~2.5°. In this way, by matching visual and echo-based contributions to object discrimination, we can estimate the quality of echoacoustic information that transfers to other sensory modalities, predict theoretical bounds on perception, and inform the design of assistive techniques and technology available for blind individuals.

Dataset Information

Skeletal descriptions of shape provide unique perceptual information for object recognition.

Publications

Skeletal descriptions of shape provide unique perceptual information for object recognition.

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