The lawful imprecision of human surface tilt estimation in natural scenes

Kim, Seha; Burge, Johannes

doi:10.7554/elife.31448

Cited by 31 publications

(51 citation statements)

References 54 publications

(69 reference statements)

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“…64 unique cue values), as computed from the natural image database. We have previously verified that quantizing the cue values is not a primary limiting factor on the performance of the model [16]. C Pooling local estimates in a spatial pooling region centered on a target location.…”

Section: Local Signed Tilt Estimationmentioning

confidence: 72%

“…tilt) is correlated across space. Unfortunately, the correlation of circular (i.e., angular) variables is notoriously unstable when the variables are highly dispersed, and it is known that local tilt in natural scenes is a highly dispersed circular variable [16]. This fact makes it difficult to precisely link measured scene statistics to optimal pooling rules.…”

Section: Natural Scene Statistics Of Tiltmentioning

confidence: 99%

“…The display system creates retinal images that provide a close approximation to the retinal images and stereo-viewing geometry that viewing the original scene would have created [16]. On each trial, the observer viewed a scene location through a 3º diameter circular stereoscopic window.…”

Section: Psychophysical Experimentsmentioning

confidence: 99%

“…In recent years, a series of papers have provided evidence linking certain statistical aspects of natural images and scenes [15,28,[33][34][35][36][37][38] to the design of the human visual system [39][40][41], and to the performance of human observers in perceptual tasks [14,16,37,[42][43][44][45][46][47][48][49]. This broad program of research has, with varying degrees of rigor, invoked natural scene statistics to account for a strikingly diverse set of topics: how the shape of pupils changes across species in different ecological niches [41], where corresponding points are located in the two retinas [39,40], how biases in binocular eye movements manifest [48], how targets are detected in natural images [47], how image contours are perceptually grouped [37,42], how image orientation is estimated [45], how binocular disparity is estimated [44,50,51], how image motion is estimated [46,49,52], how 3D tilt is estimated [16], and now, how cues to 3D tilt are pooled across space. Over this same period, numerous modeling frameworks have emerged that provide theoretical and computational methods for predicting and accounting for these links [50,[53]…”

Section: Visual Systems and The Internalization Of Natural Scene Statmentioning

confidence: 99%

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Natural scene statistics predict how humans pool information across space in the estimation of surface tilt

Kim

Burge

2019

Preprint

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Visual systems estimate the three-dimensional (3D) structure of scenes from information in twodimensional (2D) retinal images. Visual systems use multiple sources of information to improve the accuracy of these estimates, including statistical knowledge of the probable spatial arrangements of natural scenes. Here, we examine how 3D surface tilts are spatially related in real-world scenes, and show that humans pool information across space when estimating surface tilt in accordance with these spatial relationships. We develop a hierarchical model of surface tilt estimation that is grounded in the statistics of tilt in natural scenes and images. The model computes a global tilt estimate by pooling local tilt estimates within an adaptive spatial neighborhood. The spatial neighborhood in which local estimates are pooled changes according to the value of the local estimate at a target location. The hierarchical model provides more accurate estimates of groundtruth tilt in natural scenes and provides a better account of human performance than the local model. Taken together, the results imply that the human visual system pools information about surface tilt across space in accordance with natural scene statistics.

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Section: Local Signed Tilt Estimationmentioning

confidence: 72%

Section: Natural Scene Statistics Of Tiltmentioning

confidence: 99%

Section: Psychophysical Experimentsmentioning

confidence: 99%

Section: Visual Systems and The Internalization Of Natural Scene Statmentioning

confidence: 99%

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Natural scene statistics predict how humans pool information across space in the estimation of surface tilt

Kim

Burge

2019

Preprint

Self Cite

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“…The same appeal to natural statistics could be invoked to explain the difficulty in perceiving expansion or contraction in depth of solid objects (Johansson, 1964;Jansson & Johansson, 1973;Jain & Zaidi, 2011), while other deformations are easy to discern, even for rotating and flowing shapes (Cohen, Jain & Zaidi, 2010;Fantoni, Caudek & Domini, 2014;Bates et al, 2019). However, the slant illusion is just as compelling in the static case, so biases in perceiving depth versus extent from retinal images may also be in play (Jain & Zaidi, 2013;Kim & Burge 2018). Although not a part of this study, we want to note that perceived slant is also affected by other factors, such as object shape.…”

Section: Resultsmentioning

confidence: 98%

Mental geometry of 3D size and shape perception

Zaidi

Maruya

2019

Preprint

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Judging poses, sizes and shapes of objects accurately is necessary for organisms and machines to operate successfully in the world. Retinal images of 3D objects are mapped by the rules of projective geometry, and preserve the invariants of that geometry. Since Plato, it has been debated whether geometry is innate to the human brain, and Poincare and Einstein thought it worth examining whether formal geometry arises from experience with the world. We examine if humans have learned to exploit projective geometry to estimate sizes and shapes of objects in 3D scenes.Numerous studies have examined size invariance as a function of physical distance, which changes scale on the retina, but surprisingly, possible constancy or inconstancy of relative size seems not to have been investigated for object pose, which changes retinal image size differently along different axes. We show systematic underestimation of length for extents pointing towards or away from the observer, both for static objects and dynamically rotating objects. Observers do correct for projected shortening according to the optimal back-transform, obtained by inverting the projection function, but the correction is inadequate by a multiplicative factor. The clue is provided by the greater underestimation for longer objects, and the observation that they appear more slanted towards the observer. Adding a multiplicative factor for perceived slant in the back-transform model provides good fits to the corrections used by observers. We quantify the slant illusion with relative slant measurements, and use a dynamic demonstration to show the power of the slant illusion.In biological and mechanical objects, distortions of shape are manifold, and changes in aspect ratio and relative limb sizes are functionally important. Our model shows that observers try to retain invariance of these aspects of shape to 3D rotation by correcting retinal image distortions due to perspective projection, but the corrections can fall short. We discuss how these results imply that humans have internalized particular aspects of projective geometry through evolution or learning, and how assuming that images are preserving the continuity, collinearity, and convergence invariances of projective geometry, supplements the Generic Viewpoint assumption, and simply explains other illusions, such as Ames' Chair.

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Validation of the hind feet position score and its association with heel height difference in dairy cows

Hund,

Reiter,

Huber

et al. 2024

Vet Res Commun

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Hind feet position scoring (HFPS) categorizes the outward rotation of the hind feet from the line parallel to the midline of the body in standing dairy cows. It has previously been used as an indication of both differences in heel height between the lateral and medial hind claw (to determine the need of hoof trimming) and the presence of claw lesions in sound cattle. In this observational study, the agreement of HFPS with other types of hoof angle measurements, as well as its association with the heel height difference (HHD) between the claws were investigated.A total of 51 dairy cows were assessed independently by three observers in two measuring rounds on two different measuring days each. On each occasion, they scored the HFPS, and measured the angle of outward rotation of both hind feet using a digital protractor (DIG) and a compass app (COMP). Heel height difference was measured only during the second occasion. Intra- and interobserver agreement were calculated using weighted kappa statistics (HFPS) and intraclass correlation (DIG, COMP and HHD). Associations between HFPS and DIG, COMP and HHD were analyzed using linear mixed models.Intra- and interobserver reliability were poor to good for HFPS, DIG, COMP and HHD. HFPS was significantly associated with DIG and COMP but not with HHD. Using the median value of repeated HFPS scores could increase the robustness of the HFPS assessment, as our data indicate that the cows frequently shift the position of their hind claws. Overall, there was a poor correlation between HHD and HFPS, so HFPS may not be determined by HHD alone; future research should consider other reasons for outward rotation of the hind feet.

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The lawful imprecision of human surface tilt estimation in natural scenes

Cited by 31 publications

References 54 publications

Natural scene statistics predict how humans pool information across space in the estimation of surface tilt

Natural scene statistics predict how humans pool information across space in the estimation of surface tilt

Mental geometry of 3D size and shape perception

Validation of the hind feet position score and its association with heel height difference in dairy cows

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