The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.
Saliency, attention, and visual search: An information theoretic approach
Open accessAbstract
A proposal for saliency computation within the visual cortex is put forth based on the premise that localized saliency computation serves to maximize information sampled from one's environment. The model is built entirely on computational constraints but nevertheless results in an architecture with cells and connectivity reminiscent of that appearing in the visual cortex. It is demonstrated that a variety of visual search behaviors appear as emergent properties of the model and therefore basic principles of coding and information transmission. Experimental results demonstrate greater efficacy in predicting fixation patterns across two different data sets as compared with competing models.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
A feature-integration theory of attention.
Treisman, A. M., & Gelade, G. (1980) · Cognitive Psychology · doi:10.1016/0010-0285(80)90005-5 · Cited by 12,366
A model of saliency-based visual attention for rapid scene analysis
Itti, L., Koch, C., & Niebur, E. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.730558 · Cited by 11,271
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
Olshausen, B. A., & Field, D. J. (1996) · Nature · doi:10.1038/381607a0 · Cited by 5,694
Forest before trees: The precedence of global features in visual perception
Navon, D. (1977) · Cognitive Psychology · doi:10.1016/0010-0285(77)90012-3 · Cited by 4,005
The Handbook of brain theory and neural networks
(1996) · Choice Reviews Online · doi:10.5860/choice.33-4484 · Cited by 3,870
Shifts in Selective Visual Attention: Towards the Underlying Neural Circuitry
Koch, C., & Ullman, S. (1987) · Matters of Intelligence · doi:10.1007/978-94-009-3833-5_5 · Cited by 3,722
Visual search and stimulus similarity.
Duncan, J., & Humphreys, G. W. (1989) · Psychological Review · doi:10.1037/0033-295x.96.3.433 · Cited by 3,563
IARBUS, A. L. (1967) · Medical Entomology and Zoology · Cited by 3,319
Some informational aspects of visual perception.
Attneave, F. (1954) · Psychological Review · doi:10.1037/h0054663 · Cited by 2,890
Emotion drives attention: Detecting the snake in the grass.
Öhman, A., Flykt, A., & Esteves, F. (2001) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.130.3.466 · Cited by 2,542
To See or not to See: The Need for Attention to Perceive Changes in Scenes
Rensink, R. A., O'Regan, J. K., & Clark, J. J. (1997) · Psychological Science · doi:10.1111/j.1467-9280.1997.tb00427.x · Cited by 2,338
Feature analysis in early vision: Evidence from search asymmetries.
Treisman, A., & Gormican, S. (1988) · Psychological Review · doi:10.1037//0033-295x.95.1.15 · Cited by 2,257
The “independent components” of natural scenes are edge filters
Bell, A. J., & Sejnowski, T. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00121-1 · Cited by 2,201
Guided search: An alternative to the feature integration model for visual search.
Wolfe, J. M., Cave, K. R., & Franzel, S. L. (1989) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037//0096-1523.15.3.419 · Cited by 2,147
Lee, T.-W., Girolami, M., & Sejnowski, T. J. (1999) · Neural Computation · doi:10.1162/089976699300016719 · Cited by 1,967
What attributes guide the deployment of visual attention and how do they do it?
Wolfe, J. M., & Horowitz, T. S. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1411 · Cited by 1,766 · cited 1×
“An example of this modeled on the experiment of Duncan and Humphreys (1989) and based on the example shown in Wolfe and Horowitz (2004) is shown in Figure 10 (top).”
Torralba, A., Oliva, A., Castelhano, M. S., & Henderson, J. M. (2006) · Psychological Review · doi:10.1037/0033-295x.113.4.766 · Cited by 1,639
Modeling the role of salience in the allocation of overt visual attention
Parkhurst, D., Law, K., & Niebur, E. (2002) · Vision Research · doi:10.1016/s0042-6989(01)00250-4 · Cited by 1,388
Eye movements in natural behavior
Hayhoe, M., & Ballard, D. (2005) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2005.02.009 · Cited by 1,326
SUN: A Bayesian framework for saliency using natural statistics
Zhang, L., Tong, M. H., Marks, T. K., Shan, H., & Cottrell, G. W. (2008) · Journal of Vision · doi:10.1167/8.7.32 · Cited by 1,227
Bayesian surprise attracts human attention
Itti, L., & Baldi, P. (2009) · Vision Research · doi:10.1016/j.visres.2008.09.007 · Cited by 1,224
High-Order Contrasts for Independent Component Analysis
Cardoso, J.-F. (1999) · Neural Computation · doi:10.1162/089976699300016863 · Cited by 1,213
Modeling visual attention via selective tuning
Tsotsos, J. K., Culhane, S. M., Kei Wai, W. Y., Lai, Y., Davis, N., & Nuflo, F. (1995) · Artificial Intelligence · doi:10.1016/0004-3702(95)00025-9 · Cited by 1,143
Self-citationSaliency Based on Information Maximization
Bruce, N. D. B., & Tsotsos, J. K. (2005) · neural information processing systems · Cited by 1,134
Self-citationIndependent component filters of natural images compared with simple cells in primary visual cortex
van Hateren, J. H., & van der Schaaf, A. (1998) · Proceedings of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rspb.1998.0303 · Cited by 1,106
The Roles of Vision and Eye Movements in the Control of Activities of Daily Living
Land, M., Mennie, N., & Rusted, J. (1999) · Perception · doi:10.1068/p2935 · Cited by 1,094
Involvement of striate and extrastriate visual cortical areas in spatial attention
Martínez, A., Anllo-Vento, L., Sereno, M. I., Frank, L. R., Buxton, R. B., Dubowitz, D. J., Wong, E. C., Hinrichs, H., Heinze, H. J., & Hillyard, S. A. (1999) · Nature Neuroscience · doi:10.1038/7274 · Cited by 936
Functional localization of the system for visuospatial attention using positron emission tomography
Nobre, A. (1997) · Brain · doi:10.1093/brain/120.3.515 · Cited by 900
Optimal eye movement strategies in visual search
Najemnik, J., & Geisler, W. S. (2005) · Nature · doi:10.1038/nature03390 · Cited by 848
Object-based attention in the primary visual cortex of the macaque monkey
Roelfsema, P. R., Lamme, V. A. F., & Spekreijse, H. (1998) · Nature · doi:10.1038/26475 · Cited by 814
What Can 1 Million Trials Tell Us About Visual Search?
Wolfe, J. M. (1998) · Psychological Science · doi:10.1111/1467-9280.00006 · Cited by 717
Visual correlates of fixation selection: effects of scale and time
Tatler, B. W., Baddeley, R. J., & Gilchrist, I. D. (2005) · Vision Research · doi:10.1016/j.visres.2004.09.017 · Cited by 700
Could information theory provide an ecological theory of sensory processing?
Atick, J. J. (2011) · Network: Computation in Neural Systems · doi:10.3109/0954898x.2011.638888 · Cited by 679
Perception of shape from shading
Ramachandran, V. S. (1988) · Nature · doi:10.1038/331163a0 · Cited by 674
A saliency map in primary visual cortex
Li, Z. (2002) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01817-9 · Cited by 660
Functional MRI reveals spatially specific attentional modulation in human primary visual cortex
Somers, D. C., Dale, A. M., Seiffert, A. E., & Tootell, R. B. H. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.4.1663 · Cited by 653
Adaptive Rescaling Maximizes Information Transmission
Brenner, N., Bialek, W., & de Ruyter van Steveninck, R. (2000) · Neuron · doi:10.1016/s0896-6273(00)81205-2 · Cited by 647
A coherent computational approach to model bottom-up visual attention
Le Meur, O., Le Callet, P., Barba, D., & Thoreau, D. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.86 · Cited by 642
Visual memory and motor planning in a natural task
Hayhoe, M. M., Shrivastava, A., Mruczek, R., & Pelz, J. B. (2003) · Journal of Vision · doi:10.1167/3.1.6 · Cited by 567
Algorithms for defining visual regions-of-interest: comparison with eye fixations
Privitera, C. M., & Stark, L. W. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.877520 · Cited by 535
van Hateren, J. H., & Ruderman, D. L. (1998) · Proceedings of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rspb.1998.0577 · Cited by 407
Familiarity and pop-out in visual search
Wang, Q., Cavanagh, P., & Green, M. (1994) · Perception & Psychophysics · doi:10.3758/bf03206946 · Cited by 348
Verghese, P. (2001) · Neuron · doi:10.1016/s0896-6273(01)00392-0 · Cited by 348
Surfaces versus features in visual search
He, Z. J., & Nakayama, K. (1992) · Nature · doi:10.1038/359231a0 · Cited by 304
At first sight: A high-level pop out effect for faces
Hershler, O., & Hochstein, S. (2005) · Vision Research · doi:10.1016/j.visres.2004.12.021 · Cited by 296
Perception of Objects in Natural Scenes: Is It Really Attention Free?
Evans, K. K., & Treisman, A. (2005) · Journal of Experimental Psychology: Human Perception and Performance · doi:10.1037/0096-1523.31.6.1476 · Cited by 281
On the information extracted from a glance at a scene.
Biederman, I., Rabinowitz, J. C., Glass, A. L., & Stacy, E. W. (1974) · Journal of Experimental Psychology · doi:10.1037/h0037158 · Cited by 279
Effect of Non-Target Stimuli upon Length of Voluntary Saccades
Coren, S., & Hoenig, P. (1972) · Perceptual and Motor Skills · doi:10.2466/pms.1972.34.2.499 · Cited by 277
Visual attention as a multilevel selection process
KASTNER, S., & PINSK, M. A. (2004) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/cabn.4.4.483 · Cited by 260
Hopf, J.-M., Boehler, C. N., Luck, S. J., Tsotsos, J. K., Heinze, H.-J., & Schoenfeld, M. A. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507746103 · Cited by 253
Self-citationDetecting conjunctions of color and form: Reassessing the serial search hypothesis
Pashler, H. (1987) · Perception & Psychophysics · doi:10.3758/bf03208218 · Cited by 240
A simple saliency model predicts a number of motion popout phenomena
Rosenholtz, R. (1999) · Vision Research · doi:10.1016/s0042-6989(99)00077-2 · Cited by 235
Object-centered not scene-based visual neglect.
Tipper, S. P., & Behrmann, M. (1996) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.22.5.1261 · Cited by 219
Where to look next? Eye movements reduce local uncertainty
Renninger, L. W., Verghese, P., & Coughlan, J. (2007) · Journal of Vision · doi:10.1167/7.3.6 · Cited by 191
Sparse coding in the primate cortex
Földiák, P., & Young, M. P. (1998) · St Andrews Research Repository (St Andrews Research Repository) · Cited by 183
Perception of Letters in Words: Seek Not and Ye Shall Find
Johnston, J. C., & McClelland, J. L. (1974) · Science · doi:10.1126/science.184.4142.1192 · Cited by 159
Confidence Intervals for the Area Under the ROC Curve
Cortes, C., & Mohri, M. (2004) · neural information processing systems · Cited by 158
Characterizing the Limits of Human Visual Awareness
Huang, L., Treisman, A., & Pashler, H. (2007) · Science · doi:10.1126/science.1143515 · Cited by 150
Müller, M. M., & Hübner, R. (2002) · Psychological Science · doi:10.1111/1467-9280.00422 · Cited by 147
Chromatic structure of natural scenes
Wächtler, T., Lee, T.-W., & B, T. J. S. A. (2001) · Journal of the Optical Society of America A · doi:10.1364/josaa.18.000065 · Cited by 134
Search asymmetries? What search asymmetries?
Rosenholtz, R. E. (2001) · Perception & Psychophysics · doi:10.3758/bf03194414 · Cited by 117
The effect of spatial configuration on surround suppression of contrast sensitivity
Petrov, Y., & McKee, S. P. (2006) · Journal of Vision · doi:10.1167/6.3.4 · Cited by 114
Visual search asymmetry: The influence of stimulus familiarity and low-level features
Shen, J., & Reingold, E. M. (2001) · Perception & Psychophysics · doi:10.3758/bf03194413 · Cited by 110
With a careful look: Still no low-level confound to face pop-out
Hershler, O., & Hochstein, S. (2006) · Vision Research · doi:10.1016/j.visres.2006.03.023 · Cited by 80
Parallel processing of park-whole information in visual search tasks
Wolfs, J. M., Friedman‐Hill, S. R., & Bilsky, A. B. (1994) · Perception & Psychophysics · doi:10.3758/bf03205311 · Cited by 79
Preattentive Vision and Perceptual Groups
Bravo, M. J., & Blake, R. (1990) · Perception · doi:10.1068/p190515 · Cited by 77
Rosenholtz, R. (2001) · Journal of Experimental Psychology: Human Perception and Performance · doi:10.1037//0096-1523.27.4.985 · Cited by 68 · cited 3×
“For example, a horizontally oriented bar among distractors at 30 degrees is much more salient than a horizontal bar among distractors 1/3 oriented at 30 degrees, 1/3 at 50 degrees, and 1/3 at 70 degrees as observed in Rosenholtz (2001a).”
BackgroundResultOn the Consistency and the Power of Wilcoxon’s two Sample Test
van Dantzig, D. (1951) · Indagationes Mathematicae (Proceedings) · doi:10.1016/s1385-7258(51)50001-x · Cited by 64
The effect of background color on asymmetries in color search
Rosenholtz, R. E., Nagy, A. L., & Bell, N. R. (2004) · Journal of Vision · doi:10.1167/4.3.9 · Cited by 54
Features that draw visual attention: an information theoretic perspective
Bruce, N. D. B. (2004) · Neurocomputing · doi:10.1016/j.neucom.2004.10.065 · Cited by 52
Self-citationCue‐invariant detection of centre–surround discontinuity by V1 neurons in awake macaque monkey
Shen, Z., Xu, W., & Li, C. (2007) · The Journal of Physiology · doi:10.1113/jphysiol.2007.130294 · Cited by 49
Shuren, J. E., Jacobs, D. H., & Heilman, K. M. (1997) · Brain and Cognition · doi:10.1006/brcg.1997.0918 · Cited by 43
Cited by
Attention, uncertainty, and free-energy
Feldman, H., & Friston, K. J. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00215 · Cited by 1,365
Eye guidance in natural vision: reinterpreting salience
Tatler, B. W., Hayhoe, M. M., Land, M. F., & Ballard, D. H. (2011) · Journal of Vision · doi:10.1167/11.5.5 · Cited by 775
Active inference and epistemic value
Friston, K., Rigoli, F., Ognibene, D., Mathys, C., Fitzgerald, T., & Pezzulo, G. (2015) · Cognitive Neuroscience · doi:10.1080/17588928.2015.1020053 · Cited by 731
Jiang, M., Huang, S., Duan, J., & Zhao, Q. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298710 · Cited by 729
Metadata
- Authors
- Bruce, N. D. B., & Tsotsos, J. K.
- Venue
- Journal of Vision
- Published
- 2009-03-01
- Volume
- 9
- Issue
- 3
- Pages
- 5-5
- ISSN
- 1534-7362 (ISSN-L)
- OpenAlex
- W2103666701
- Cited by
- 855
- References
- 74
- FWCI
- 68.16
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.