Capabilities and Limitations of Peripheral Vision

Rosenholtz, Ruth

doi:10.1146/annurev-vision-082114-035733

Cited by 283 publications

(278 citation statements)

References 91 publications

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“…Scenes that we recognize as distinct places might have identical layout and it is the textures and object ensembles that provide the crucial cues to where we are. Scene perception mostly happens in the peripheral visual field, which is limited by visual acuity but especially by visual crowding (Rosenholtz, 2016). PPA may extract the identity of the scene by encoding the summary statistics of object ensembles present in the scene (Cant and Xu, 2012).…”

Section: Discussionmentioning

confidence: 99%

Rapid invariant encoding of scene layout in human OPA

Henriksson

Mur

Kriegeskorte

2019

Preprint

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Successful visual navigation requires a sense of the geometry of the local environment.How do our brains extract this information from retinal images? Here we visually presented scenes with all possible combinations of five scene-bounding elements (left, right and back wall, ceiling, floor) to human subjects during functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). The fMRI response patterns in the scene-responsive occipital place area (OPA) reflected scene layout with invariance to changes in surface texture. This result contrasted sharply with the primary visual cortex (V1), which reflected low-level image features of the stimuli, and parahippocampal place area (PPA), which showed better texture than layout decoding.MEG indicated that the texture-invariant scene-layout representation is computed from visual input within ~100 ms, suggesting a rapid computational mechanism. Taken together, these results suggest that the cortical representation underlying our instant sense of the environmental geometry is located in OPA. ) for assistance with the measurements. We acknowledge the computational resources provided by the Aalto Science-IT project.

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Section: Discussionmentioning

confidence: 99%

Rapid invariant encoding of scene layout in human OPA

Henriksson

Mur

Kriegeskorte

2019

Preprint

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“…Recent studies examining the perceptual discrimination of natural textures further showed that two textures are perceptually indistinguishable (become a metameric pair) in peripheral vision when they are matched not only in terms of V1 image statistics, but also in terms of the joint statistics of V1 responses, to which V2 and the higher cortical areas are responsive Freeman et al, 2013;Ziemba et al, 2016). Human observers can visually discriminate V2 metamer textures (with identical Gabor and joint statistics), but only when using elaborated attentive spatial processing by central vision (Freeman et al, 2013;Rosenholtz, 2016).…”

Section: Introductionmentioning

confidence: 99%

Haptic metameric textures

Kuroki

Sawayama

Nishida

2019

Preprint

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The ability to recognize and discriminate complex surface textures through touch is essential to the survival of living beings, including humans. Most studies of tactile texture perception have emphasized perceptual impacts of lower-order statistical structures of stimulus surfaces that can be described in terms of amplitude spectra or spatial-frequency/orientation subband histograms (e.g., root mean squares of carving depth and inter-ridge distance). However, real-world surfaces we encounter in everyday life differ also in higher-order statistics that appear in phase spectra or joint subband histograms. Though human vision has sensitivity to higher-order statistics, and some studies have revealed similarities between visual and tactile information processing, it remains obscure whether human touch has sensitivity to higher-order statistics. Here we show that patterns different from each other in higher-order statistics, which can be easily distinguished by vision, cannot be distinguished by touch. We 3D-printed textured surfaces transcribed from different 'photos' of natural scenes such as stones and leaves. The textures look sufficiently different, and the maximum carving depth (2 mm) was well above the haptic detection threshold. Nevertheless, observers (n=10) could not accurately discriminate some texture pairs. Analysis of these stimuli showed that the more similar the amplitude spectrum was, the more difficult the discrimination became, suggesting a hypothesis that the highorder statistics have minor effects on tactile texture discrimination. We directly tested this hypothesis by matching the subband histogram of each texture using a texture synthesis algorithm. Haptic discrimination of these textures was found to be nearly impossible, although visual discrimination remained feasible due to differences in higher-order statistics. These findings suggest that human tactile texture perception qualitatively differs from visual texture perception with regard to insensitivity to higher-order statistical differences. SignificanceHumans sense spatial patterns in the surrounding world through their eyes and hands. Researchers have revealed a detailed hierarchical processing of image features for visual texture perception, while that for haptic texture perception remains obscure. One big bottleneck in tactile research has been difficulty in controlling stimulus patterns, but this issue is being resolved by recent technological progress. Here we move a step ahead by using a high-resolution 3D printer. We invented textured surfaces that were 3D-printed from visual images, and controlled low-and high-order statistics of the surfaces by changing features of the original images. Behavioural experiments showed that human observers have sensitivity to lower-order statistics, which is in line with previous studies, but we could not observe any positive evidence of sensitivity to higher-order statistics. Although recent studies have emphasized the similarity between touch to vision with regard to spatiotemporal processing, th...

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“…Our ability to recognise objects declines sharply in peripheral vision (1). This is not simply due to resolution or acuity -objects that are visible in isolation become indistinguishable when other objects fall within surrounding 'interference zones' (2)(3)(4).…”

Section: Introductionmentioning

confidence: 99%

Dissociable effects of visual crowding on the perception of colour and motion

Greenwood

Parsons

2019

Preprint

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Our ability to recognise objects in peripheral vision is fundamentally limited by crowding, the deleterious effect of clutter that disrupts the recognition of features ranging from orientation and colour to motion and depth. Prior research is equivocal on whether this reflects a singular process that disrupts all features simultaneously or multiple processes that affect each independently. We examined crowding for motion and colour, two features that allow a strong test of feature independence. 'Cowhide' stimuli were presented 15 degrees in peripheral vision, either in isolation or surrounded by flankers to give crowding. Observers reported either the target hue (blue/purple) or its direction (clockwise/counterclockwise from upwards). We first established that both features show systematic crowded errors (predominantly biased towards the flanker identities) and selectivity for target-flanker similarity (with reduced crowding for dissimilar target/flanker elements). The multiplicity of crowding was then tested with observers identifying both features: a singular object-selective mechanism predicts that when crowding is weak for one feature and strong for the other that crowding should be all-or-none for both. In contrast, when crowding was weak for colour and strong for motion, errors were reduced for colour but remained for motion, and vice versa with weak motion and strong colour crowding. This double dissociation follows the predictions of independent crowding processes, suggesting that crowding can disrupt vision in a feature-specific manner. The ability to recognise one aspect of a cluttered scene, like colour, thus offers no guarantees for the correct recognition of other aspects, like motion. Significance statementThe fundamental limitation on our peripheral vision is crowding, the disruptive effect of image clutter on object recognition. Crowding is widely assumed to be a singular process, affecting all of the features (e.g. orientation, motion, and colour) within an object simultaneously. In contrast, we find a double dissociation for these disruptions: observers can make errors in judging the colour of a crowded object whilst correctly judging its movement direction, and vice versa. This dissociation is well described by a population-coding model that independently pools the motion and colour of target and flanker elements. We suggest that crowding may be a generic set of processes distributed throughout the visual system that independently simplify the representation of our visual field.

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Capabilities and Limitations of Peripheral Vision

Cited by 283 publications

References 91 publications

Rapid invariant encoding of scene layout in human OPA

Rapid invariant encoding of scene layout in human OPA

Haptic metameric textures

Dissociable effects of visual crowding on the perception of colour and motion

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