Can people detect errors in shadows and reflections?
Open accessAbstract
The increasing sophistication of photo-editing software means that even amateurs can create compelling doctored images. Yet recent research suggests that people's ability to detect image manipulations is limited. Given the prevalence of manipulated images in the media, on social networking sites, and in other domains, the implications of mistaking a fake image as real, or vice versa, can be serious. In seven experiments, we tested whether people can make use of errors in shadows and reflections to determine whether or not an image has been manipulated. Our results revealed that people's ability to identify authentic and manipulated scenes based on shadow and reflection information increased with the size of the manipulation, but overall, detection rates remained poor. Consistent with theories of incomplete visual representation, one possible reason for these findings could be that people rarely encode the details of scenes that provide useful cues as to the authenticity of images. Overall, our findings indicate that people do not readily make use of shadow and reflection cues to help determine the authenticity of images-yet it remains possible that people could make use of these cues, but they are simply unaware of how to do so.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Past work in the cognitive science of media forensics has demonstrated that people are not good at perceiving and reasoning about shadow, reflection, and other physical implausibility cues.
“Past work in the cognitive science of media forensics has demonstrated that people are not good at perceiving and reasoning about shadow, reflection, and other physical implausibility cues (9–12).”
From Deepfake detection by human crowds, machines, and machine-informed crowds (2022) · cites this paper as [10]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Longitudinal data analysis using generalized linear models
LIANG, K.-Y., & ZEGER, S. L. (1986) · Biometrika · doi:10.1093/biomet/73.1.13 · Cited by 18,550 · see citing works
The New Statistics: Why and How
Cumming, G. (2014) · Psychological Science · doi:10.1177/0956797613504966 · Cited by 3,200 · see citing works
Kajiya, J. T. (1986) · ACM SIGGRAPH Computer Graphics · doi:10.1145/15886.15902 · Cited by 2,258 · see citing works
(2011) · Cited by 2,025 · see citing works
Longitudinal Data Analysis Using Generalized Linear Models
Liang, K., & Zeger, S. L. (1986) · Biometrika · doi:10.2307/2336267 · Cited by 1,201 · see citing works
Do “brain-training” programs work?
Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016) · Psychological Science in the Public Interest · doi:10.1177/1529100616661983 · Cited by 1,183 · see citing works
Simons, D. J., & Levin, D. T. (1997) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(97)01080-2 · Cited by 1,039 · see citing works
Familiarity and visual change detection
Pashler, H. (1988) · Perception & Psychophysics · doi:10.3758/bf03210419 · Cited by 1,024 · see citing works
Qualitative Descriptors of Strength of Association and Effect Size
Rosenthal, J. A. (1996) · Journal of Social Service Research · doi:10.1300/j079v21n04_02 · Cited by 941 · see citing works
Rensink, R. A. (2002) · Annual Review of Psychology · doi:10.1146/annurev.psych.53.100901.135125 · Cited by 850 · see citing works
Kajiya, J. T. (1986) · ACM SIGGRAPH Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) · doi:10.1145/15922.15902 · Cited by 849 · see citing works
Learning, Attentional Control, and Action Video Games
Green, C. S., & Bavelier, D. (2012) · Current Biology · doi:10.1016/j.cub.2012.02.012 · Cited by 713 · see citing works
Learning hatching for pen-and-ink illustration of surfaces
Kalogerakis, E., Nowrouzezahrai, D., Breslav, S., & Hertzmann, A. (2012) · ACM Transactions on Graphics · doi:10.1145/2077341.2077342 · Cited by 653 · see citing works
Seeing, sensing, and scrutinizing
Rensink, R. A. (2000) · Vision Research · doi:10.1016/s0042-6989(00)00003-1 · Cited by 483 · see citing works
A picture is worth a thousand lies: Using false photographs to create false childhood memories
Wade, K. A., Garry, M., Read, J. D., & Lindsay, D. S. (2002) · Psychonomic Bulletin & Review · doi:10.3758/bf03196318 · Cited by 469 · see citing works
Self-citationExample-guided physically based modal sound synthesis
Ren, Z., Yeh, H., & Lin, M. C. (2013) · ACM Transactions on Graphics · doi:10.1145/2421636.2421637 · Cited by 455 · see citing works
In Sight, Out of Mind: When Object Representations Fail
Simons, D. J. (1996) · Psychological Science · doi:10.1111/j.1467-9280.1996.tb00378.x · Cited by 379 · see citing works
Influence of Scene-Based Properties on Visual Search
Enns, J. T., & Rensink, R. A. (1990) · Science · doi:10.1126/science.2300824 · Cited by 270 · see citing works
Perceiving Illumination Inconsistencies in Scenes
Ostrovsky, Y., Cavanagh, P., & Sinha, P. (2005) · Perception · doi:10.1068/p5418 · Cited by 145 · see citing works
Perceptual learning in visual search: Fast, enduring, but non-specific
Sireteanu, R., & Rettenbach, R. (1995) · Vision Research · doi:10.1016/0042-6989(94)00295-w · Cited by 143 · see citing works
Gravity and observer's body orientation influence the visual perception of human body postures
Christophe Lopez, A., Bachofner, C., Mercier, M. R., & Blanke, O. (2009) · Journal of Vision · doi:10.1167/9.5.1 · Cited by 135 · see citing works
Can people identify original and manipulated photos of real-world scenes?
Nightingale, S. J., Wade, K. A., & Watson, D. G. (2017) · Cognitive Research: Principles and Implications · doi:10.1186/s41235-017-0067-2 · Cited by 135 · see citing works
Self-citationExposing photo manipulation with inconsistent reflections
O’Brien, J. F., & Farid, H. (2012) · ACM Transactions on Graphics · doi:10.1145/2077341.2077345 · Cited by 131 · see citing works
Self-citationFarid, H. (2016) · The MIT Press eBooks · doi:10.7551/mitpress/10451.001.0001 · Cited by 129 · see citing works
Self-citationChanging history: doctored photographs affect memory for past public events
Sacchi, D. L. M., Agnoli, F., & Loftus, E. F. (2007) · Applied Cognitive Psychology · doi:10.1002/acp.1394 · Cited by 118 · see citing works
Perceptual learning in visual search generalizes over tasks, locations, and eyes
Sireteanu, R., & Rettenbach, R. (2000) · Vision Research · doi:10.1016/s0042-6989(00)00145-0 · Cited by 110 · see citing works
Exposing photo manipulation with inconsistent shadows
Kee, E., O’Brien, J. F., & Farid, H. (2013) · ACM Transactions on Graphics · doi:10.1145/2487228.2487236 · Cited by 101 · see citing works
Self-citationWhy the visual recognition system might encode the effects of illumination
Tarr, M. J., Kersten, D., & Bülthoff, H. (1998) · Vision Research · doi:10.1016/s0042-6989(98)00041-8 · Cited by 100 · see citing works
The Influence of Cast Shadows on Visual Search
Rensink, R. A., & Cavanagh, P. (2004) · Perception · doi:10.1068/p5322 · Cited by 90 · see citing works
The nature of light : an historical survey
Ronchi, V. (1970) · Medical Entomology and Zoology · Cited by 76 · see citing works
Image forensic analyses that elude the human visual system
Farid, H., & Bravo, M. J. (2010) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.837788 · Cited by 68 · see citing works
Self-citationNeural bandwidth of veridical perception across the visual field
Wilkinson, M. O., Anderson, R. S., Bradley, A., & Thibos, L. N. (2016) · Journal of Vision · doi:10.1167/16.2.1 · Cited by 63 · see citing works
Impossible Shadows and the Shadow Correspondence Problem
Mamassian, P. (2004) · Perception · doi:10.1068/p5280 · Cited by 61 · see citing works
Naive optics: Predicting and perceiving reflections in mirrors.
Bertamini, M., Spooner, A. L. R., & Hecht, H. (2003) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.29.5.982 · Cited by 60 · see citing works
Perceptual learning in visual search: Some evidence of specificities
Ellison, A., & Walsh, V. (1998) · Vision Research · doi:10.1016/s0042-6989(97)00195-8 · Cited by 50 · see citing works
Naive optics: Understanding the geometry of mirror reflections.
Croucher, C. J., Bertamini, M., & Hecht, H. (2002) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037//0096-1523.28.3.546 · Cited by 46 · see citing works
What makes cast shadows hard to see?
Porter, G. (2010) · Journal of Vision · doi:10.1167/10.3.13 · Cited by 45 · see citing works
The Shadow Knows: A Primer on the Informational Structure of Cast Shadows
Casati, R. (2004) · Perception · doi:10.1068/p5281 · Cited by 44 · see citing works
The Perception and Content of Cast Shadows: An Interdisciplinary Review
Dee, H., & Santos, P. E. (2011) · Spatial Cognition and Computation · doi:10.1080/13875868.2011.565396 · Cited by 43 · see citing works
Naive optics: Understanding the geometry of mirror reflections.
Croucher, C. J., Bertamini, M., & Hecht, H. (2002) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.28.3.546 · Cited by 36 · see citing works
Errors in Judging Information about Reflections in Mirrors
Lawson, R., & Bertamini, M. (2006) · Perception · doi:10.1068/p5498 · Cited by 35 · see citing works
Can fabricated evidence induce false eyewitness testimony?
Wade, K. A., Green, S. L., & Nash, R. A. (2009) · Applied Cognitive Psychology · doi:10.1002/acp.1607 · Cited by 32 · see citing works
Self-citationSearch for gross illumination discrepancies in images of natural objects
Lovell, P. G., Gilchrist, I. D., Tolhurst, D., & Troscianko, T. (2009) · Journal of Vision · doi:10.1167/9.1.37 · Cited by 29 · see citing works
Naive Optics: Acting on Mirror Reflections.
Hecht, H., Bertamini, M., & Gamer, M. (2005) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.31.5.1023 · Cited by 27 · see citing works
Changing beliefs about past public events with believable and unbelievable doctored photographs
Nash, R. A. (2017) · Memory · doi:10.1080/09658211.2017.1364393 · Cited by 26 · see citing works
Khang, B.-G., Koenderink, J. J., & Kappers, A. M. L. (2006) · Perception · doi:10.1068/p5485 · Cited by 25 · see citing works
Shadows as Sources of Cues for Distance of Shadow-Casting Objects
Allen, B. P. (1999) · Perceptual and Motor Skills · doi:10.2466/pms.1999.89.2.571 · Cited by 24 · see citing works
Measuring the perception of light inconsistencies
López‐Moreno, J., Sundstedt, V., Sangorrin, F., & Gutiérrez, D. (2010) · Symposium on Applied Perception in Graphics and Visualization (APGV) · doi:10.1145/1836248.1836252 · Cited by 23 · see citing works
Effects of scene content and layout on the perceived light direction in 3D spaces
Xia, L., Pont, S. C., & Heynderickx, I. E. J. (2016) · Journal of Vision · doi:10.1167/16.10.14 · Cited by 19 · see citing works
Through the looking-glass: Objects in the mirror are less real
Sareen, P., Ehinger, K. A., & Wolfe, J. M. (2014) · Psychonomic Bulletin & Review · doi:10.3758/s13423-014-0761-8 · Cited by 14 · see citing works
What fits into a mirror: Naïve beliefs about the field of view.
Bianchi, I., & Savardi, U. (2012) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/a0027035 · Cited by 12 · see citing works
The Perception of Lighting Inconsistencies in Composite Outdoor Scenes
Tan, M., Lalonde, J., Sharan, L., Rushmeier, H., & O’Sullivan, C. (2015) · ACM Transactions on Applied Perception · doi:10.1145/2810038 · Cited by 11 · see citing works
Change blindness for cast shadows in natural scenes: Even informative shadow changes are missed
Ehinger, K. A., Allen, K., & Wolfe, J. M. (2016) · Attention Perception & Psychophysics · doi:10.3758/s13414-015-1054-7 · Cited by 11 · see citing works
People cannot locate the projection of an object on the surface of a mirror
Lawson, R. (2010) · Cognition · doi:10.1016/j.cognition.2009.12.013 · Cited by 5 · see citing works
Testing the Egocentric Mirror-Rotation Hypothesis
Muelenz, C., Gamer, M., & Hecht, H. (2010) · Seeing and Perceiving · doi:10.1163/187847510x540000 · Cited by 5 · see citing works
Montague, J. (1985) · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Hecht E Zajac A Optics 1974 Reading, MA Addison-Wesley
Cited by
Sorted by citations
Deepfake detection by human crowds, machines, and machine-informed crowds
Groh, M., Epstein, Z., Firestone, C., & Picard, R. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2110013119 · Cited by 248 · see citing works
Nightingale, S. J., Wade, K. A., & Watson, D. G. (2022) · Psychology and Aging · doi:10.1037/pag0000682 · Cited by 15 · see citing works
Self-citationIdentifying and minimising the impact of fake visual media: Current and future directions
Nightingale, S. J., & Wade, K. A. (2022) · Memory Mind & Media · doi:10.1017/mem.2022.8 · Cited by 14 · see citing works
Self-citationFoley, M. A. (2020) · Review of General Psychology · doi:10.1177/1089268020958686 · Cited by 12 · see citing works
General lighting can overcome accidental viewing
Bülthoff, I., Breidt, M., Bülthoff, H., & Kersten, D. (2023) · i-Perception · doi:10.1177/20416695231215604 · Cited by 8 · see citing works
Mijatović, A., Žuljević, M. F., Ursić, L., Bralić, N., Vuković, M., Roguljić, M., & Marušić, A. (2025) · Research Integrity and Peer Review · doi:10.1186/s41073-025-00172-0 · Cited by 4 · see citing works
Visual attention in change blindness for objects and shadows
Hermens, F., & Zdravković, S. (2022) · Perception · doi:10.1177/03010066221109936 · Cited by 2 · see citing works
Estimating lighting direction in scenes with multiple objects
Peterson, L. M., Kersten, D., & Mannion, D. J. (2023) · Attention Perception & Psychophysics · doi:10.3758/s13414-023-02718-0 · Cited by 2 · see citing works
Human sensory adaptation to the ecological structure of environmental statistics
Neri, P. (2024) · Journal of Vision · doi:10.1167/jov.24.3.3 · Cited by 2 · see citing works
#Filterdrop: Attending to Photographic Alterations
Anscomb, C. (2023) · The Nordic Journal of Aesthetics · doi:10.7146/nja.v32i65-66.140109 · Cited by 2 · see citing works
Cooper, E. A., Casati, R., Farid, H., & Cavanagh, P. (2023) · Journal of Vision · doi:10.1167/jov.23.8.13 · Cited by 1 · see citing works
Self-citationTracking Reflected Objects: A Benchmark
Guo, X., Zhong, P., Lin, L., Zhang, H., Huang, L., & Li, S. (2024) · Lecture notes in computer science · doi:10.1007/978-981-96-0901-7_21 · Cited by 2 · see citing works
Estimating lighting direction in scenes with multiple objectsPreprint
Peterson, L. M., Kersten, D., & Mannion, D. J. (2022) · doi:10.31234/osf.io/txy5u
Assessing shadows and reflections consistency in AI-generated images
Bianchi, S., Iuliani, M., Paghera, A., Fontani, M., & Jerian, M. (2024) · IEEE International Workshop on Information Forensics and Security · doi:10.1109/wifs61860.2024.10810725
- Authors
- Nightingale, S. J., Wade, K. A., Farid, H., & Watson, D. G.
- Affiliations
- University of Warwick (GB)
- Dartmouth College (US)
- Corresponding author
- Nightingale, Sophie J.
- Venue
- Attention, Perception, & Psychophysics
- Published
- 2019-06-28
- Volume
- 81
- Issue
- 8
- Pages
- 2917-2943
- ISSN
- 1943-3921 (ISSN-L)
- 1943-393X
- PMC
- PMC6856028
- OpenAlex
- W2955138768
- Cited by
- 14
- References
- 55
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 4 · 2022: 4 · 2021: 1 · 2020: 1
- FWCI
- 0.67
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Attention Perception & Psychophysics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion, cc-by)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Funders
- University of Warwick
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- image forgery detection, image editing, image authenticity, visual perception, scene encoding
- MeSH terms
- Adolescent, Adult, Cues, Depth Perception, Female, Humans, Judgment, Male, Middle Aged, Photic Stimulation, Young Adult
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
