scholarly journals Crowding effects in central and peripheral vision when viewing natural scenes

2010 ◽  
Vol 9 (8) ◽  
pp. 1038-1038
Author(s):  
M. P. S. To ◽  
I. D. Gilchrist ◽  
T. Troscianko ◽  
P. G. Lovell ◽  
D. J. Tolhurst
2011 ◽  
Vol 51 (14) ◽  
pp. 1686-1698 ◽  
Author(s):  
M.P.S. To ◽  
I.D. Gilchrist ◽  
T. Troscianko ◽  
D.J. Tolhurst

2020 ◽  
Vol 10 (9) ◽  
pp. 596
Author(s):  
Lisa V. Eberhardt ◽  
Anke Huckauf

Depth needs to be considered to understand visual information processing in cluttered environments in the wild. Since differences in depth depend on current gaze position, eye movements were avoided by short presentations in a real depth setup. Thus, allowing only peripheral vision, crowding was tested. That is, the impairment of peripheral target recognition by the presence of nearby flankers was measured. Real depth was presented by a half-transparent mirror that aligned the displays of two orthogonally arranged, distance-adjustable screens. Fixation depth was at a distance of 190 cm, defocused depth planes were presented either near or far, in front of or behind the fixation depth, all within the depth of field. In Experiments 1 and 2, flankers were presented defocused, while the to-be-identified targets were on the fixation depth plane. In Experiments 3–5, targets were presented defocused, while the flankers were kept on the fixation depth plane. Results for defocused flankers indicate increased crowding effects with increased flanker distance from the target at focus (near to far). However, for defocused targets, crowding for targets in front of the focus as compared to behind was increased. Thus, defocused targets produce decreased crowding with increased target distance from the observer. To conclude, the effects of flankers in depth seem to be centered around fixation, while effects of target depth seem to be observer-centered.


2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Andrew M Haun

Abstract It is sometimes claimed that because the resolution and sensitivity of visual perception are better in the fovea than in the periphery, peripheral vision cannot support the same kinds of colour and sharpness percepts as foveal vision. The fact that a scene nevertheless seems colourful and sharp throughout the visual field then poses a puzzle. In this study, I use a detailed model of human spatial vision to estimate the visibility of certain properties of natural scenes, including aspects of colourfulness, sharpness, and blurriness, across the visual field. The model is constructed to reproduce basic aspects of human contrast and colour sensitivity over a range of retinal eccentricities. I apply the model to colourful, complex natural scene images, and estimate the degree to which colour and edge information are present in the model’s representation of the scenes. I find that, aside from the intrinsic drift in the spatial scale of the representation, there are not large qualitative differences between foveal and peripheral representations of ‘colourfulness’ and ‘sharpness’.


i-Perception ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 204166952199415
Author(s):  
Ryan V. Ringer ◽  
Allison M. Coy ◽  
Adam M. Larson ◽  
Lester C. Loschky

Visual crowding, the impairment of object recognition in peripheral vision due to flanking objects, has generally been studied using simple stimuli on blank backgrounds. While crowding is widely assumed to occur in natural scenes, it has not been shown rigorously yet. Given that scene contexts can facilitate object recognition, crowding effects may be dampened in real-world scenes. Therefore, this study investigated crowding using objects in computer-generated real-world scenes. In two experiments, target objects were presented with four flanker objects placed uniformly around the target. Previous research indicates that crowding occurs when the distance between the target and flanker is approximately less than half the retinal eccentricity of the target. In each image, the spacing between the target and flanker objects was varied considerably above or below the standard (0.5) threshold to either suppress or facilitate the crowding effect. Experiment 1 cued the target location and then briefly flashed the scene image before participants could move their eyes. Participants then selected the target object’s category from a 15-alternative forced choice response set (including all objects shown in the scene). Experiment 2 used eye tracking to ensure participants were centrally fixating at the beginning of each trial and showed the image for the duration of the participant’s fixation. Both experiments found object recognition accuracy decreased with smaller spacing between targets and flanker objects. Thus, this study rigorously shows crowding of objects in semantically consistent real-world scenes.


2017 ◽  
Author(s):  
David W. Hunter ◽  
Paul B. Hibbard

AbstractVisual acuity is greatest in the centre of the visual field, peaking in the fovea and degrading significantly towards the periphery. The rate of decay of visual performance with eccentricity depends strongly on the stimuli and task used in measurement. While detailed measures of this decay have been made across a broad range of tasks, a comprehensive theoretical account of this phenomenon is lacking. We demonstrate that the decay in visual performance can be attributed to the efficient encoding of binocular information in natural scenes. The efficient coding hypothesis holds that the early stages of visual processing attempt to form an efficient coding of ecologically valid stimuli. Using Independent Component Analysis to learn an efficient coding of stereoscopic images, we show that the ratio of binocular to monocular components varied with eccentricity at the same rate as human stereo acuity and Vernier acuity. Our results demonstrate that the organisation of the visual cortex is dependent on the underlying statistics of binocular scenes and, strikingly, that monocular acuity depends on the mechanisms by which the visual cortex processes binocular information. This result has important theoretical implications for understanding the encoding of visual information in the brain.


1995 ◽  
Author(s):  
S.N. Yendrikhovskij ◽  
H. DE Ridder ◽  
E.A. Fedorovskaya

Author(s):  
Thomas E. Moriarty ◽  
Andrew M. Junker ◽  
Don R. Price

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