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Roland William Fleming

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Roland William Fleming
Roland William Fleming standing in his office in 2019
Born (1978-03-01) 1 March 1978 (age 46)
NationalityBritish and German
EducationNew College School
Magdalen College School
Alma materUniversity of Oxford (BA)
Massachusetts Institute of Technology (PhD)
Known forVisual perception of materials and objects
AwardsVSS Young Investigator Award (2013)
FRSB
Scientific career
Fields
InstitutionsMax Planck Institute for Biological Cybernetics
Justus Liebig University of Giessen
Thesis Human Visual Perception under Real-world Illumination  (2004)
Doctoral advisorEdward H. Adelson
Websitewww.allpsych.uni-giessen.de/fleminglab/

Roland William Fleming, FRSB (born 1978 in Oxford, UK) is a British and German interdisciplinary researcher specializing in the visual perception of objects and materials. He is the Kurt Koffka Professor of Experimental Psychology at Justus Liebig University of Giessen.[1] and the Executive Director of the Center for Mind, Brain and Behavior of the Universities of Marburg and Giessen.[2] He is also co-Spokesperson for the Research Cluster “The Adaptive Mind”.[3]

Biography

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Fleming was educated at New College School and Magdalen College School in Oxford. Thereafter, he was a student at New College, University of Oxford, where he studied for a Bachelor’s degree in Psychology, Philosophy and Physiology. He graduated with First Class Honours in 1999.[4] He then studied for a Doctorate at the Department of Brain and Cognitive Sciences at MIT, graduating in 2004. His doctoral thesis “Human Visual Perception under Real-World Illumination” was supervised by Edward H. Adelson.[5]

In 2003, he took up a post-doctoral research position at the Max Planck Institute for Biological Cybernetics, working in the department of Heinrich H. Bülthoff.[6] From 2009–2013 he served as co-Editor-In-Chief of the journal ACM Transactions on Applied Perception.[7] In 2010, moved to the Justus Liebig University of Giessen to become the Kurt Koffka Junior Professor of Experimental Psychology.[1] From 2013–2016,[8] Fleming coordinated the Marie Curie Initial Training Network “PRISM: Perceptual Representation of Illumination, Shape and Material”.[9] From 2016–2022 he ran the ERC Consolidator Grant “SHAPE: On the Perception of Growth, Form and Process”.[10] He received tenure in 2016 and was promoted to Full Professor in 2020.[4] In 2021 he became the Executive Director of the Centre for Mind, Brain and Behavior at the Universities of Marburg and Giessen. In 2022 he was elected Fellow of the Royal Society of Biology.[11] Fleming has served on the Expert Review Group and the Interview Panel for the Wellcome Trust.[12] In 2023 he was awarded the ERC Advanced Grant “STUFF: Perceiving Materials and their Properties”.[13]

Honors and awards

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In 2012, Fleming was awarded the Faculty Research Prize of the Justus Liebig University of Giessen (“Preis der Justus-Liebig-Universität Gießen”) for his work on the visual estimation of 3D shape from image orientations.[14] In 2013, he was awarded the Elsevier/Vision Sciences Society Young Investigator Award.[15] In 2016 he was awarded an ERC Consolidator Grant “SHAPE: On the Perception of Growth, Form and Process”[10] and in 2023 an ERC Advanced Grant “STUFF: Perceiving Materials and their Properties”.[13] In 2021, he delivered the Vision Sciences Society annual Public Lecture.[16] In 2022 he was elected Fellow of the Royal Society of Biology.[11]

Research

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Fleming specializes in the human visual perception of materials and objects, and their physical properties.[1] He is particularly known for his contributions to establishing material perception as a field of study in vision science.[15][17][18][19] He uses a combination of research methods from experimental psychology, computational neuroscience, computer graphics and machine learning.[4]

Material Perception

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Fleming’s early works focused on the visual perception of the optical properties of surfaces and materials, such as gloss,[20] translucency[21] and transparency.[22] He helped determine the role of visual cues such as motion [23] and binocular stereopsis [24][25][26] in the perception of surface reflectance, especially gloss. A recurring theme within this work was the concept that specular reflections behave unlike surface markings—such as pigmentation patterns or scratches—leading to specific visual cues for identifying specular reflections and therefore glossy surfaces. He also investigated how multi-component patterns of specular reflection lead to hazy glossy appearances.[27] His more recent studies on surface appearance have tested whether artificial neural networks can reproduce the patterns of errors and successes that human observers make when judging material properties.[28][29][30]

In addition to studying how the visual system estimates optical properties of materials, he has also investigated the relationship between other material properties and material categories, and how these are affected by the viewing distance, as in the so-called ‘material-scale ambiguity’.[31]

Fleming also led a number of studies on how the visual system infers the mechanical properties of materials, such as compliance,[32] elasticity,[33] and viscosity [34][35] [36] [37] from optical, shape and motion cues.[38][39] Most of these studies used finite elements computer simulations of liquids or deformable solids interacting with their surroundings. A recurring theme within this body of work is the idea that the visual system represents stimuli in a multi-dimensional space of midlevel visual features, which statistically characterize how shape, motion and appearance evolve over time. He and his colleagues have claimed that such representations facilitate disentangling intrinsic material properties from other factors that also contribute to the proximal stimulus[19][36] such as a flowing liquid’s speed, or the force deforming a compliant solid.

Early in his career, Fleming argued that the visual system infers material properties through heuristics, using simple image statistics that correlate with surface properties under typical viewing conditions.[5][20][21] Later however, he proposed that the visual system uses richer internal models of the appearance of objects and materials under typical viewing conditions—an idea he calls ‘Statistical Appearance Models'.[17][40] Specifically, he has suggested that the visual system acquires the ability to infer material properties (or other distal stimulus properties) by learning generative models of proximal stimuli through unsupervised learning objectives, such as compressing or predictive coding of image content.[41][42] A proof-of-concept of this theory was demonstrated by training an unsupervised artificial neural network model on a dataset of computer rendered images of bumpy, glossy surfaces.[43] Fleming and his colleagues found that the model spontaneously learned to disentangle scene variables—such as lighting and surface reflectance—even though it was given no explicit information about the true values of these variables. Moreover, the model correctly predicted both successes and failures (i.e., illusions) of human gloss perception.

Shape Perception

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Fleming’s early works focused on the visual estimation of three-dimensional (3D) shape from specular reflections,[44][45] shading [46][47] and texture.[48] He is particularly known as a proponent of the role of ‘orientation fields’ in shape perception.[49][50] Orientation fields refer to spatially varying patterns of the dominant local orientation across the image of a surface, as measured by populations of orientation-selective neurons at each image location.[46][44][45][47][48] Fleming and his colleagues have shown that local image orientation signals tend to vary smoothly across curved surfaces in ways that are systematically related to 3D shape properties.[51] For textured surfaces, local image orientation is related to first-order shape properties, especially surface slant and tilt.[48] For shading patterns and specular reflections, local image orientation structure is related to second-order shape properties, especially the direction of minimum second derivative of surface depths, and the ratio of minimum and maximum second derivative magnitudes.[44][47] He has argued that orientation fields provide a fundamental source of information about shape,[52][53][54] and that their use by the visual system predicts specific illusions of perceived shape, such as when illumination changes.[55]

In addition to the visual estimation of 3D shape, Fleming has also investigated the perceptual organization of shape[56][57] and the use of shape to make additional inferences about objects and their properties,[32][33][34][36][58]—a process he calls ‘Shape Understanding’.[10] Fleming led a number of studies on how the visual system makes inferences about the processes and transformations that have formed objects or altered their shape.[59][60][61][62][63][64][65] A recurring theme within this body of work is that an object’s ‘causal history’ leaves traces in its shape, which can be used to identify which of its features are the result of shape-altering transformations.[60][62] Such transformations include simple spatial distortions[59][60] and more complex biological growth processes.[61] By analogy to the visual system’s ability to separate images depicting transparent surfaces into multiple distinct causes, Fleming and his colleagues refer to the separation of shape into distinct causes as ‘Shape Scission’.[65] An example of this is the ability to distinguish the causes of different shape features that occur when a face or object is fully covered with a cloth veil.[66] Some of the visible features of the surface of the cloth are caused by the textile draping of its own accord, while others are due to the protrusion of the underlying object. Observers can distinguish these causes, even when the hidden object is of unknown shape.[66]

Fleming has also investigated the role of shape in object categorization, especially in one-shot learning of novel object categories from a single (or small number of) exemplars.[67][68] In this context, Fleming and colleagues developed a computational model for predicting the perceived similarity between pairs of two-dimensional (2D) shapes, called ‘ShapeComp’.[69] The model combines a large number of shape features to capture different aspects of shape. He and his colleagues have also studied how shape cues contribute to the visual perception of animacy,[70] and conversely how semantics alter the perceptual organization of shape.[71] Fleming and colleagues have argued that human visual one-shot categorization involves inferring a generative model from the exemplar object.[67][68] They have proposed that this involves segmenting the object into parts, and representing their relations in a way that can be modified to synthesize novel variants belonging to the same category as the exemplar. They claim that this idea is supported by experiments in which participants are presented with a single exemplar and are asked to draw novel variants.[68]

Computer Graphics

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Fleming’s work in computer graphics has mainly focused on perceptually-based approaches to representing and modifying photographic imagery. He contributed to the development of image-based algorithms for altering the material appearance[72] and shape[73] of objects in photographs. His work on orientation fields led to methods for synthesizing images of objects with particular 3D shape and material appearance based on purely 2D image operations.[74] He also contributed to work investigating perceptually-based methods for converting between and presenting conventional (low-dynamic range) and high-dynamic range images.[75][76] He co-authored a text book entitled “Visual Perception from a Computer Graphics Perspective”[77]

Grasping and interacting with objects and materials

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Fleming’s work on motor control has focused primarily on the effects of 3D shape[78][79][80] and material properties[79][81][82]—including mass,[81][82] friction[81][83] and rigidity[84]—on grasping. He and his colleagues have investigated various illusions related to grasping,[82][85] including the ‘material-weight illusion,[82] a variant of the size-weight illusion, in which the expected weight of an object is manipulated through its surface material (instead of its volume as in the size-weight illusion). He and his colleagues developed a computational model for predicting human precision grip (thumb and forefinger) grasp locations on objects with varying 3D shape and materials properties.[79] The model combines multiple cost functions related to the properties of the object and the actor’s hand. The model predicted average human grasp locations approximately as well as different individuals’ grasps predict one another. His research group has developed methods for measuring the contact regions between hands and objects to capture unconstrained, whole-hand grasping behavior.[86]

References

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  1. ^ a b c Fleming Lab Webpage: https://www.allpsych.uni-giessen.de/fleminglab/
  2. ^ Website of the Center for Mind, Brain and Behavior: https://www.cmbb-fcmh.de/de/cmbb-info/organisation
  3. ^ Website of The Adaptive Mind: https://www.theadaptivemind.de/governance/board-of-directors.html
  4. ^ a b c ORCID Webpage, Roland Fleming: https://orcid.org/my-orcid?orcid=0000-0001-5033-5069
  5. ^ a b Fleming’s PhD Thesis, MIT Online Repository of PhD Theses: https://dspace.mit.edu/handle/1721.1/30112
  6. ^ Max Planck Institute for Biological Cybernetics Website: https://www.kyb.tuebingen.mpg.de/84275/Alumni-AGBU
  7. ^ ACM Transactions on Applied Perception Masthead: https://dl.acm.org/action/showFmPdf?doi=10.1145%2F1462055
  8. ^ Entry for Marie Curie ITN “PRISM” on Cordis Website: https://cordis.europa.eu/project/id/316746
  9. ^ PRISM Website: https://www.allpsych.uni-giessen.de/prism/network/Admin.html
  10. ^ a b c Entry for ERC Consolidator Grant “SHAPE” on Cordis Website: https://cordis.europa.eu/project/id/682859
  11. ^ a b Online Edition of The Biologist, magazine of the Royal Society of Biology: https://ocean.exacteditions.com/issues/99541/spread/39
  12. ^ Website of the Wellcome Trust, List of Members of the Interview Panel: https://wellcome.org/grant-funding/guidance/funding-application-advisory-committees/science-interview-panel
  13. ^ a b "ERC Advanced Grants 2022 List of Principal Investigators selected for funding" (PDF).
  14. ^ Justus Liebig University Giessen website: Table of winners of the faculty research prize:  https://www.uni-giessen.de/org/admin/stab/stf/dl/preise/tabelle_pjlu
  15. ^ a b Vision Sciences Society Website, Young Investigator Award, 2013: https://www.visionsciences.org/2013-yia/
  16. ^ Vision Sciences Society Website, Annual Public Lecture, 2021:  https://www.visionsciences.org/2021-public-lecture/
  17. ^ a b Fleming, Roland W. (2014). "Visual Perception of Materials and their Properties". Vision Research. 94: 62–75. doi:10.1016/j.visres.2013.11.004. PMID 24291494. S2CID 18018810.
  18. ^ Fleming, RW; Gegenfurtner, KR; Nishida, S (2015). "Visual perception of materials: The science of stuff". Vision Research. 109: 123–124. doi:10.1016/j.visres.2015.01.014. PMID 25625527. S2CID 12312577.
  19. ^ a b Fleming, RW (2017). "Material Perception". Annual Review of Vision Science. 3 (1): 365–388. doi:10.1146/annurev-vision-102016-061429. PMID 28697677.
  20. ^ a b Fleming, RW; Dror, RO; Adelson, EH (2003). "Real world illumination and the perception of surface reflectance properties". Journal of Vision. 3 (5): 347–368. doi:10.1167/3.5.3. PMID 12875632.
  21. ^ a b Fleming, RW; Bülthoff, HH (2005). "Low-level image cues in the perception of translucent materials". ACM Transactions on Applied Perception. 2 (3): 346–382. doi:10.1145/1077399.1077409. S2CID 18765054.
  22. ^ Fleming, RW; Jäkel, F; Maloney, LT (2011). "Visual Perception of Thick Transparent Materials". Psychological Science. 22 (6): 812–820. doi:10.1177/0956797611408734. PMID 21597102. S2CID 5934256.
  23. ^ Doerschner, K; Fleming, RW; Yilmaz, O; Schrater, PR; Hartung, B; Kersten, D (2011). "Visual Motion and the Perception of Surface Material". Current Biology. 21 (23): 1–7. Bibcode:2011CBio...21.2010D. doi:10.1016/j.cub.2011.10.036. PMC 3246380. PMID 22119529.
  24. ^ Murry, A; Welchman, AE; Blake, A; Fleming, RW (2013). "Specular reflections and the estimation of shape from binocular disparity". Proceedings of the National Academy of Sciences. 110 (6): 2413–2418. Bibcode:2013PNAS..110.2413M. doi:10.1073/pnas.1212417110. PMC 3568321. PMID 23341602.
  25. ^ Murry, A; Fleming, RW; Welchman, AE (2014). "Key characteristics of specular stereo". Journal of Vision. 14 (14): 14. doi:10.1167/14.14.14. PMC 4278431. PMID 25540263.
  26. ^ Murry, A; Fleming, RW; Welchman, AE (2016). "'Proto-rivalry': how the binocular brain identifies gloss". Proc. R. Soc. B. 283 (1830). doi:10.1098/rspb.2016.0383. PMC 4874713. PMID 27170713.
  27. ^ Vangorp, P; Barla, P; Fleming, RW (2017). "The perception of hazy gloss". Journal of Vision. 17 (5): 19. doi:10.1167/17.5.19. PMID 28558395. S2CID 26091530.
  28. ^ Storrs, KR; Anderson, BL; Fleming, RW (2021). "Unsupervised learning predicts human perception and misperception of gloss". Nature Human Behaviour. 5 (10): 1402–1417. doi:10.1038/s41562-021-01097-6. PMC 8526360. PMID 33958744.
  29. ^ Prokott, KE; Tamura, H; Fleming, RW (2021). "Gloss perception: Searching for a deep neural network that behaves like humans". Journal of Vision. 21 (12): 14. doi:10.1167/jov.21.12.14. PMC 8626854. PMID 34817568.
  30. ^ Tamura, H; Prokott, KE; Fleming, RW (2021). "Distinguishing mirror from glass: A 'big data' approach to material perception". Journal of Vision. 22 (4): 4. doi:10.1167/jov.22.4.4. PMC 8934559. PMID 35266961.
  31. ^ Cheeseman, JR; Fleming, RW; Schmidt, F (2022). "Scale Ambiguities in Material Perception". iScience. 25 (3): 103970. doi:10.1016/j.isci.2022.103970. PMC 8914553. PMID 35281732.
  32. ^ a b Paulun, VC; Schmidt, F; Van Assen, JJ; Fleming, RW (2017). "Shape, motion and optical cues to stiffness of elastic objects". Journal of Vision. 17 (1): 1–22. doi:10.1167/17.1.20. PMID 28114494.
  33. ^ a b Paulun, VC; Fleming, RW (2020). "Visually inferring elasticity from the motion trajectory of bouncing cubes". Journal of Vision. 20 (6): 6. doi:10.1167/jov.20.6.6. PMC 7416883. PMID 32516356.
  34. ^ a b Paulun, VC; Kawabe, T; Nishida, S; Fleming, RW (2015). "Seeing liquids from static snapshots". Vision Research. 115 (Pt B): 163–174. doi:10.1016/j.visres.2015.01.023. PMID 25676882. S2CID 8166492.
  35. ^ Kawabe, T; Maruya, K; Fleming, RW; Nishida, S (2015). "Seeing liquids from visual motion". Vision Research. 109(B): 125–138. doi:10.1016/j.visres.2014.07.003. PMID 25102388. S2CID 18228658.
  36. ^ a b c Van Assen, JJ; Barla, P; Fleming, RW (2018). "Visual Features in the Perception of Liquids". Current Biology. 28 (3): 452–458. Bibcode:2018CBio...28E.452V. doi:10.1016/j.cub.2017.12.037. PMC 5807092. PMID 29395924.
  37. ^ Van Assen, JJ; Nishida, S; Fleming, RW (2020). "Visual perception of liquids: Insights from deep neural networks". PLOS Computational Biology. 16 (8): e1008018. Bibcode:2020PLSCB..16E8018V. doi:10.1371/journal.pcbi.1008018. PMC 7437867. PMID 32813688.
  38. ^ Van Assen, JJ; Fleming, RW (2016). "Influence of optical material properties on the perception of liquids". Journal of Vision. 16 (12): 12. doi:10.1167/16.15.12. PMID 27973644.
  39. ^ Schmidt, F; Paulun, VC; Van Assen, JJ; Fleming, RW (2017). "Inferring the stiffness of unfamiliar objects from optical, shape, and motion cues". Journal of Vision. 17 (18): 18. doi:10.1167/17.3.18. PMID 28355630.
  40. ^ Roland Fleming’s lecture at the Shitsukan Symposium, Tokyo, July 2014: https://www.youtube.com/watch?v=UDLqxukmqkY
  41. ^ Storrs, KR; Fleming, RW (2021). "Learning About the World by Learning About Images". Current Directions in Psychological Science. 30 (2): 120–128. doi:10.1177/0963721421990334. S2CID 233430117.
  42. ^ Fleming, RW; Storrs, KR (2019). "Learning to See Stuff". Current Opinion in Behavioral Sciences. 30 (30): 100–108. doi:10.1016/j.cobeha.2019.07.004. PMC 6919301. PMID 31886321.
  43. ^ Storrs, KR; Anderson, BL; Fleming, RW (2021). "Unsupervised learning predicts human perception and misperception of gloss". Nature Human Behaviour. 5 (10): 1402–1417. doi:10.1038/s41562-021-01097-6. PMC 8526360. PMID 33958744.
  44. ^ a b c Fleming, Roland W.; Torralba, Antonio; Adelson, Edward H. (2004-08-02). "Specular reflections and the perception of shape". Journal of Vision. 4 (9): 798–820. doi:10.1167/4.9.10. ISSN 1534-7362. PMID 15493971.
  45. ^ a b Weidenbacher, Ulrich; Bayerl, Pierre; Neumann, Heiko; Fleming, Roland (2006-07-01). "Sketching shiny surfaces: 3D shape extraction and depiction of specular surfaces". ACM Transactions on Applied Perception. 3 (3): 262–285. doi:10.1145/1166087.1166094. ISSN 1544-3558. S2CID 1492355.
  46. ^ a b Fleming, Roland W. (Roland William) (2004). Human visual perception under real-world illumination (Thesis thesis). Massachusetts Institute of Technology. hdl:1721.1/30112.
  47. ^ a b c Adelson, Edward H.; Torralba, Antonio; Fleming, Roland W. (2009-10-22). "Shape from Sheen". hdl:1721.1/49511. {{cite journal}}: Cite journal requires |journal= (help)
  48. ^ a b c Fleming, Roland W.; Holtmann-Rice, Daniel; Bülthoff, Heinrich H. (2011-12-20). "Estimation of 3D shape from image orientations". Proceedings of the National Academy of Sciences. 108 (51): 20438–20443. Bibcode:2011PNAS..10820438F. doi:10.1073/pnas.1114619109. ISSN 0027-8424. PMC 3251077. PMID 22147916.
  49. ^ "Preisträgerinnen und Preisträger ab dem Jahr 1976". Justus-Liebig-Universität Gießen (in German).
  50. ^ "VSS 2013 Young Investigator – Roland W. Fleming".
  51. ^ Cholewiak, Steven; Vergne, Romain; Kunsberg, Benjamin; Zucker, Steven; Fleming, Roland (2015-09-01). "Distinguishing between texture and shading flows for 3D shape estimation". Journal of Vision. 15 (12): 965. doi:10.1167/15.12.965. ISSN 1534-7362.
  52. ^ Fleming, Roland W. (2010-08-01). "From local image measurements to 3D shape". Journal of Vision. 10 (7): 2. doi:10.1167/10.7.2. ISSN 1534-7362.
  53. ^ Fleming, Roland; Li, Yuanzhen; Adelson, Edward (2008-05-02). "Image statistics for 3D shape estimation". Journal of Vision. 8 (6): 76. doi:10.1167/8.6.76. ISSN 1534-7362.
  54. ^ Fleming, Roland W.; Bülthoff, Heinrich H. (2005-09-01). "Orientation fields in the perception of 3D shape". Journal of Vision. 5 (8): 525. doi:10.1167/5.8.525. ISSN 1534-7362.
  55. ^ Fleming, Roland; Vergne, Romain; Zucker, Steven (2013-07-02). "Predicting the effects of illumination in shape from shading". Journal of Vision. 13 (9): 611. doi:10.1167/13.9.611. ISSN 1534-7362.
  56. ^ Anderson, Barton L.; Singh, Manish; Fleming, Roland W. (2002-03-01). "The Interpolation of Object and Surface Structure". Cognitive Psychology. 44 (2): 148–190. doi:10.1006/cogp.2001.0765. ISSN 0010-0285. PMID 11863323. S2CID 13862953.
  57. ^ Spröte, Patrick; Fleming, Roland W. (2013-12-01). "Concavities, negative parts, and the perception that shapes are complete". Journal of Vision. 13 (14): 3. doi:10.1167/13.14.3. ISSN 1534-7362. PMID 24306852.
  58. ^ Schmidt, Filipp; Fleming, Roland W.; Valsecchi, Matteo (2020-06-03). "Softness and weight from shape: Material properties inferred from local shape features". Journal of Vision. 20 (6): 2. doi:10.1167/jov.20.6.2. ISSN 1534-7362. PMC 7416911. PMID 32492099.
  59. ^ a b Schmidt, Filipp; Spröte, Patrick; Fleming, Roland W. (2016-09-01). "Perception of shape and space across rigid transformations". Vision Research. Quantitative Approaches in Gestalt Perception. 126: 318–329. doi:10.1016/j.visres.2015.04.011. ISSN 0042-6989. PMID 25937375. S2CID 205662957.
  60. ^ a b c Spröte, Patrick; Fleming, Roland W. (2016-09-01). "Bent out of shape: The visual inference of non-rigid shape transformations applied to objects". Vision Research. Quantitative Approaches in Gestalt Perception. 126: 330–346. doi:10.1016/j.visres.2015.08.009. ISSN 0042-6989. PMID 26386343. S2CID 3568661.
  61. ^ a b Schmidt, Filipp; Fleming, Roland W. (2016-11-01). "Visual perception of complex shape-transforming processes". Cognitive Psychology. 90: 48–70. doi:10.1016/j.cogpsych.2016.08.002. ISSN 0010-0285. PMID 27631704. S2CID 67271.
  62. ^ a b Spröte, Patrick; Schmidt, Filipp; Fleming, Roland W. (2016-11-08). "Visual perception of shape altered by inferred causal history". Scientific Reports. 6 (1): 36245. Bibcode:2016NatSR...636245S. doi:10.1038/srep36245. ISSN 2045-2322. PMC 5099969. PMID 27824094.
  63. ^ Schmidt, Filipp; Fleming, Roland W. (2018-08-16). "Identifying shape transformations from photographs of real objects". PLOS ONE. 13 (8): e0202115. Bibcode:2018PLoSO..1302115S. doi:10.1371/journal.pone.0202115. ISSN 1932-6203. PMC 6095529. PMID 30114202.
  64. ^ Fleming, Roland W.; Schmidt, Filipp (2019-04-01). "Getting "fumpered": Classifying objects by what has been done to them". Journal of Vision. 19 (4): 15. doi:10.1167/19.4.15. ISSN 1534-7362. PMID 30952166. S2CID 96448278.
  65. ^ a b Schmidt, Filipp; Phillips, Flip; Fleming, Roland W. (2019-08-01). "Visual perception of shape-transforming processes: 'Shape Scission'". Cognition. 189: 167–180. doi:10.1016/j.cognition.2019.04.006. ISSN 0010-0277. PMID 30986590. S2CID 109941237.
  66. ^ a b Phillips, Flip; Fleming, Roland W. (2020-05-26). "The Veiled Virgin illustrates visual segmentation of shape by cause". Proceedings of the National Academy of Sciences. 117 (21): 11735–11743. Bibcode:2020PNAS..11711735P. doi:10.1073/pnas.1917565117. ISSN 0027-8424. PMC 7260992. PMID 32414926.
  67. ^ a b Morgenstern, Yaniv; Schmidt, Filipp; Fleming, Roland W. (2019-12-01). "One-shot categorization of novel object classes in humans". Vision Research. 165: 98–108. doi:10.1016/j.visres.2019.09.005. ISSN 0042-6989. PMID 31707254. S2CID 207943767.
  68. ^ a b c Tiedemann, Henning; Morgenstern, Yaniv; Schmidt, Filipp; Fleming, Roland W. (2021-05-31). "One shot generalization in humans revealed through a drawing task": 2021.05.31.446461. doi:10.1101/2021.05.31.446461. S2CID 235305386. {{cite journal}}: Cite journal requires |journal= (help)
  69. ^ Morgenstern, Yaniv; Hartmann, Frieder; Schmidt, Filipp; Tiedemann, Henning; Prokott, Eugen; Maiello, Guido; Fleming, Roland W. (2021-06-01). "An image-computable model of human visual shape similarity". PLOS Computational Biology. 17 (6): e1008981. Bibcode:2021PLSCB..17E8981M. doi:10.1371/journal.pcbi.1008981. ISSN 1553-7358. PMC 8195351. PMID 34061825.
  70. ^ Schmidt, Filipp; Hegele, Mathias; Fleming, Roland W. (2017-09-01). "Perceiving animacy from shape". Journal of Vision. 17 (11): 10. doi:10.1167/17.11.10. ISSN 1534-7362. PMID 28973562.
  71. ^ Schmidt, Filipp; Kleis, Jasmin; Morgenstern, Yaniv; Fleming, Roland W. (2020-12-17). "The role of semantics in the perceptual organization of shape". Scientific Reports. 10 (1): 22141. Bibcode:2020NatSR..1022141S. doi:10.1038/s41598-020-79072-w. ISSN 2045-2322. PMC 7746709. PMID 33335146.
  72. ^ Khan, Erum Arif; Reinhard, Erik; Fleming, Roland W.; Bülthoff, Heinrich H. (2006-07-01). "Image-based material editing". ACM Transactions on Graphics. 25 (3): 654–663. doi:10.1145/1141911.1141937. hdl:11858/00-001M-0000-0013-D0DB-B. ISSN 0730-0301.
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