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Slant from texture and disparity cues: Optimal cue combination
Open accessAbstract
How does the visual system combine information from different depth cues to estimate three-dimensional scene parameters? We tested a maximum-likelihood estimation (MLE) model of cue combination for perspective (texture) and binocular disparity cues to surface slant. By factoring the reliability of each cue into the combination process, MLE provides more reliable estimates of slant than would be available from either cue alone. We measured the reliability of each cue in isolation across a range of slants and distances using a slant-discrimination task. The reliability of the texture cue increases as |slant| increases and does not change with distance. The reliability of the disparity cue decreases as distance increases and varies with slant in a way that also depends on viewing distance. The trends in the single-cue data can be understood in terms of the information available in the retinal images and issues related to solving the binocular correspondence problem. To test the MLE model, we measured perceived slant of two-cue stimuli when disparity and texture were in conflict and the reliability of slant estimation when both cues were available. Results from the two-cue study indicate, consistent with the MLE model, that observers weight each cue according to its relative reliability: Disparity weight decreased as distance and |slant| increased. We also observed the expected improvement in slant estimation when both cues were available. With few discrepancies, our data indicate that observers combine cues in a statistically optimal fashion and thereby reduce the variance of slant estimates below that which could be achieved from either cue alone. These results are consistent with other studies that quantitatively examined the MLE model of cue combination. Thus, there is a growing empirical consensus that MLE provides a good quantitative account of cue combination and that sensory information is used in a manner that maximizes the precision of perceptual estimates.
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In the citing paper
“Adults integrate texture and disparity cues to reduce the uncertainty of their estimates of slant, adjusting their relative weightings as they change in reliability (3).”
From Fusion of visual cues is not mandatory in children (2010) · cites this paper as [3]
In the citing paper
“Human adults can reduce sensory uncertainty by integrating estimates, both across modalities (1, 2) (e.g., integrating vision and touch to judge size) and within a modality (3) (e.g., integrating visual stereoscopic and texture information to judge surface slant).”
From Fusion of visual cues is not mandatory in children (2010) · cites this paper as [3]
In the citing paper
“Our assumptions and approach are based on previous more detailed validation of similar stimuli (3).”
From Fusion of visual cues is not mandatory in children (2010) · cites this paper as [3]
Citations
Cites
(1966) · Medical Entomology and Zoology · Cited by 10,293
Humans integrate visual and haptic information in a statistically optimal fashion
Ernst, M. O., & Banks, M. S. (2002) · Nature · doi:10.1038/415429a · Cited by 4,844
Self-citationComputational Geometry: Algorithms and Applications
de Berg, M., Cheong, O., van Kreveld, M. J., & Overmars, M. H. (1997) · CERN Document Server (European Organization for Nuclear Research) · Cited by 4,450
Bayesian integration in sensorimotor learning
Körding, K. P., & Wolpert, D. M. (2004) · Nature · doi:10.1038/nature02169 · Cited by 2,004
The Ventriloquist Effect Results from Near-Optimal Bimodal Integration
Alais, D., & Burr, D. (2004) · Current Biology · doi:10.1016/j.cub.2004.01.029 · Cited by 1,936
Object perception as Bayesian inference
Kersten, D., Mamassian, P., & Yuille, A. (2004) · Annual Review of Psychology · doi:10.1146/annurev.psych.55.090902.142005 · Cited by 1,269
Measurement and modeling of depth cue combination: in defense of weak fusion
Landy, M. S., Maloney, L. T., Johnston, E. B., & Young, M. (1995) · Vision Research · doi:10.1016/0042-6989(94)00176-m · Cited by 996
Self-citationGoodwin, C. (1995) · Social Studies of Science · doi:10.1177/030631295025002002 · Cited by 620
When Feeling Is More Important Than Seeing in Sensorimotor Adaptation
van Beers, R. J., Wolpert, D. M., & Haggard, P. (2002) · Current Biology · doi:10.1016/s0960-9822(02)00836-9 · Cited by 560
Researches in Binocular Vision
(1951) · JAMA · doi:10.1001/jama.1951.02920280080027 · Cited by 537
Combining Sensory Information: Mandatory Fusion Within, but Not Between, Senses
Hillis, J. M., Ernst, M. O., Banks, M. S., & Landy, M. S. (2002) · Science · doi:10.1126/science.1075396 · Cited by 486
Self-citationProblems Arising in the Analysis of a Series of Similar Experiments
Cochran, W. G. (1937) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.2307/2984123 · Cited by 444
Bayesian integration of visual and auditory signals for spatial localization
Battaglia, P., Jacobs, R. A., & Aslin, R. Ν. (2003) · Journal of the Optical Society of America A · doi:10.1364/josaa.20.001391 · Cited by 443
Do humans optimally integrate stereo and texture information for judgments of surface slant?
Knill, D. C., & Saunders, J. A. (2003) · Vision Research · doi:10.1016/s0042-6989(03)00458-9 · Cited by 415
The precision of proprioceptive position sense
van Beers, R. J., Sittig, A. C., & van der Gon, J. J. D. (1998) · Experimental Brain Research · doi:10.1007/s002210050525 · Cited by 396
Probabilistic Models of the Brain : Perception and Neural Function
Rao, R. P. N., Olshausen, B. A., & Lewicki, M. S. (2002) · Cited by 385
Optimal integration of texture and motion cues to depth
Jacobs, R. A. (1999) · Vision Research · doi:10.1016/s0042-6989(99)00088-7 · Cited by 324
Systematic distortions of shape from stereopsis
Johnston, E. B. (1991) · Vision Research · doi:10.1016/0042-6989(91)90056-b · Cited by 295
A Disparity Gradient Limit for Binocular Fusion
Burt, P. J., & Julesz, B. (1980) · Science · doi:10.1126/science.7367885 · Cited by 264
Weighted linear cue combination with possibly correlated error
Oruç, İ., Maloney, L. T., & Landy, M. S. (2003) · Vision Research · doi:10.1016/s0042-6989(03)00435-8 · Cited by 238
Self-citationA perturbation analysis of depth perception from combinations of texture and motion cues
Young, M., Landy, M. S., & Maloney, L. T. (1993) · Vision Research · doi:10.1016/0042-6989(93)90228-o · Cited by 234
Self-citationHorizontal and vertical disparity, eye position, and stereoscopic slant perception
Backus, B. T., Banks, M. S., van Ee, R., & Crowell, J. A. (1999) · Vision Research · doi:10.1016/s0042-6989(98)00139-4 · Cited by 219
Self-citationThree gradients and the perception of flat and curved surfaces.
Cutting, J. E., & Millard, R. T. (1984) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.113.2.198 · Cited by 201
Binocular contrast summation—I. Detection and discrimination
Legge, G. E. (1984) · Vision Research · doi:10.1016/0042-6989(84)90063-4 · Cited by 183
Viewing Geometry Determines How Vision and Haptics Combine in Size Perception
Gepshtein, S., & Banks, M. S. (2003) · Current Biology · doi:10.1016/s0960-9822(03)00133-7 · Cited by 168
Self-citationTHE INFLUENCE OF VISUAL ACUITY ON ACCOMMODATIVE RESPONSES OF THE EYE
Heath, G. G. (1956) · Optometry and Vision Science · doi:10.1097/00006324-195610000-00001 · Cited by 166
Why Is Spatial Stereoresolution So Low?
Banks, M. S., Gepshtein, S., & Landy, M. S. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.3852-02.2004 · Cited by 155
Self-citationIntegration of depth modules: Stereopsis and texture
Johnston, E. B., Cumming, B. G., & Parker, A. J. (1993) · Vision Research · doi:10.1016/0042-6989(93)90200-g · Cited by 152
Discrimination of planar surface slant from texture: human and ideal observers compared
Knill, D. C. (1998) · Vision Research · doi:10.1016/s0042-6989(97)00325-8 · Cited by 148
Knill, D. C. (1998) · Vision Research · doi:10.1016/s0042-6989(97)00324-6 · Cited by 147
Disparity Scaling and the Perception of Frontoparallel Surfaces
Rogers, B. J., & Bradshaw, M. F. (1995) · Perception · doi:10.1068/p240155 · Cited by 137 · cited 1×
“…Hooge, & Backus, 2001; Battaglia, Jacobs, & Aslin, 2003; Buckley & Frisby, 1993; Frisby, Buckley, & Horsman, 1995; Jacobs, 1999; Körding & Wolpert, 2004; Rogers & Bradshaw, 1995; van Beers, Sittig, & Denier van der Gon, 1998; van Beers, Wolpert, & Haggard, 2002; Young, Landy, & Maloney , 1993).”
Ideal cue combination for localizing texture-defined edges
Landy, M. S., & Kojima, H. (2001) · Journal of the Optical Society of America A · doi:10.1364/josaa.18.002307 · Cited by 137
Self-citationStereopsis, vertical disparity and relief transformations
Gårding, J., Porrill, J., Mayhew, J. E. W., & Frisby, J. P. (1995) · Vision Research · doi:10.1016/0042-6989(94)00162-f · Cited by 124
The effect of display size on disparity scaling from differential perspective and vergence cues
Bradshaw, M. F., Glennerster, A., & Rogers, B. (1996) · Vision Research · doi:10.1016/0042-6989(95)00190-5 · Cited by 121
Shape from texture: Ideal observers and human psychophysics
Blake, A., Bülthoff, H., & Sheinberg, D. L. (1993) · Vision Research · doi:10.1016/0042-6989(93)90037-w · Cited by 115
Interaction of stereo, texture and outline cues in the shape perception of three-dimensional ridges
Buckley, D., & Frisby, J. P. (1993) · Vision Research · doi:10.1016/0042-6989(93)90075-8 · Cited by 100
Blur Discrimination and its Relation to Blur-Mediated Depth Perception
Mather, G., & Smith, D. R. (2002) · Perception · doi:10.1068/p3254 · Cited by 91
Relative shear disparities and the perception of surface inclination
Howard, I. P., & Kaneko, H. (1994) · Vision Research · doi:10.1016/0042-6989(94)90237-2 · Cited by 74
Estimator Reliability and Distance Scaling in Stereoscopic Slant Perception
Backus, B. T., & Banks, M. S. (1999) · Perception · doi:10.1068/p2753 · Cited by 71
Self-citationAre corresponding points fixed?
Hillis, J. M., & Banks, M. S. (2001) · Vision Research · doi:10.1016/s0042-6989(01)00137-7 · Cited by 69
Self-citationProbabilistic Models of the Brain.
Long, D. M. (2002) · Neurosurgery Quarterly · doi:10.1097/00013414-200212000-00005 · Cited by 67
Perspective, Orientation Disparity, and Anisotropy in Stereoscopic Slant Perception
Gillam, B., & Ryan, C. (1992) · Perception · doi:10.1068/p210427 · Cited by 65
(1991) · The MIT Press eBooks · doi:10.7551/mitpress/2002.003.0015 · Cited by 54
Bayesian modeling of visual perception
Mamassian, P., Landy, M. S., & Maloney, L. T. (2002) · Cited by 49
Self-citationPerceiving slant about a horizontal axis from stereopsis
Banks, M. S., Hooge, I. T. C., & Backus, B. T. (2001) · Journal of Vision · doi:10.1167/1.2.1 · Cited by 47
Self-citationFrisby, J. P., Buckley, D., & Horsman, J. M. (1995) · Perception · doi:10.1068/p240181 · Cited by 39
van Ee, R., & Erkelens, C. J. (1998) · Vision Research · doi:10.1016/s0042-6989(97)00445-8 · Cited by 28
The stereoscopic anisotropy affects manual pointing
Hibbard, P. B., van der Willigen, R. F., Watt, Simpson, P. J., & Bradshaw, M. F. (2002) · Spatial Vision · doi:10.1163/156856802320401900 · Cited by 3
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Faisal, A. A., Selen, L. P. J., & Wolpert, D. M. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2258 · Cited by 2,883
The Bayesian brain: The role of uncertainty in neural coding and computation
Knill, D. C., & Pouget, A. (2004) · Trends in Neurosciences · doi:10.1016/j.tins.2004.10.007 · Cited by 2,588
Vergence–accommodation conflicts hinder visual performance and cause visual fatigue
Hoffman, D. M., Girshick, A. R., Akeley, K., & Banks, M. S. (2008) · Journal of Vision · doi:10.1167/8.3.33 · Cited by 1,641
Self-citationVisual Discomfort and Visual Fatigue of Stereoscopic Displays: A Review
Lambooij, M., Fortuin, M. F., Heynderickx, I. E. J., & IJsselsteijn, W. A. (2009) · Journal of Imaging Science and Technology · doi:10.2352/j.imagingsci.technol.2009.53.3.030201 · Cited by 1,006
Bayesian decision theory in sensorimotor control
Kording, K. P., & Wolpert, D. M. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.05.003 · Cited by 916
Metadata
- Authors
- Hillis, J. M., Watt, S. J., Landy, M. S., & Banks, M. S.
- Affiliations
- University of Pennsylvania (US)
- Bangor University (GB)
- New York University (US)
- University of California, Berkeley (US)
- Venue
- Journal of Vision
- Published
- 2004-12-01
- Volume
- 4
- Issue
- 12
- Pages
- 1
- ISSN
- 1534-7362 (ISSN-L)
- OpenAlex
- W2158527951
- Cited by
- 421
- References
- 48
- Citations by year
- 2026: 11 · 2025: 9 · 2024: 13 · 2023: 12 · 2022: 18 · 2021: 13 · 2020: 13 · 2019: 21 · 2018: 25 · 2017: 20 · 2016: 16 · 2015: 28 · 2014: 16 · 2013: 27 · 2012: 28
- FWCI
- 7.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Journal of Vision (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Eye Institute (R01EY012851, EY 08266, EY12851, R01EY008266)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Keywords
- surface slant perception, cue combination, binocular disparity, maximum likelihood estimation, cue reliability, perceptual precision, depth perception
- MeSH terms
- Cues, Depth Perception, Form Perception, Humans, Pattern Recognition, Visual, Vision, Binocular, Vision Disparity, Likelihood Functions
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