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THE KANIZSA TRIANGLE AS A CORNERSTONE OF VISION SCIENCE JOHAN WAGEMANS LABORATORY OF EXPERIMENTAL PSYCHOLOGY UNIVERSITY OF LEUVEN, BELGIUM KANIZSA LECTURE, TRIESTE, OCTOBER 29, 2010 Outline • Part 1: A neurocomputational model for the perception of Kanizsa figures • Part 2: Kanizsa figures in current vision science PART 2 KANIZSA FIGURES IN CURRENT VISION SCIENCE Plan for Part 2 • Some key aspects of Kanizsa phenomena • Some lessons to be drawn from them • Some examples of on-going research (in relation to Kanizsa project and beyond) • Some reflections on the current status of vision science Some key aspects of Kanizsa phenomena • Not contour completion and filling-in • But surface construction based on 2-D integration of difference signals – local depth cues (L- and T-junctions) – computation of border-ownership (edge assignment) by interactions (multiple iterations) – surface filling-in by integration – depth-lightness linkage • Depth perception = primary • Differentiation-integration = general principle Some general lessons to be drawn • All perception is construction – based on available information – constrained by general principles (ecologically valid) – does not have to be cognitive or experiencebased (autonomous organizational processes) • Surfaces are primary (Gibson, Nakayama, …) • Border-ownership is crucial • Figure-ground segregation BOWN computation Kanizsa triangle figure/ground organization depth computation 3D reconstruction More general lessons to be drawn • Phenomenology is an important point of departure – discover what needs to be explained • not necessarily a good guidance regarding mechanisms – end-point of experience may be misleading as computational starting-point • Deep and full understanding requires – implemented model (all stages, from input image to reproduced experience) – based on general (not ad hoc) neurocomputational principles (~inner and outer psychophysics) – tested in wide range of conditions (Kanizsa variation figures) (~experimental phenomenology) phenomenology, psychophysics vision sciences neurosciences computational modelling Neural mechanisms of Kanizsa figures • Some monkey single-cell neurophysiology – von der Heydt et al. (1984) – Zhou et al. (2000) – Qiu & von der Heydt (2005) • Some human fMRI – Mendola et al. (1999) V2 neurons with illusory contours von der Heydt, R. et al. (1984). Science, 224(4654), 1260-1262 Neurons in V2 show responses to illusory contour stimuli corresponding to their preferred orientation. Open question Do these neurons represent “collinearity” (FACADE model) or “BOWN as an implicit signal of surface” (DISC model)? BOWN-sensitive neurons exist in V2 Borderline-ownership sensitive neurones in V2 Zhou, H. et al. (2000). Journal of Neuroscience, 20, 6594-6611 This neuron responds stronger when the left white side is the owner of the borderline. BOWN-sensitive neurons in V2 are also Borderline-ownership sensitive neurones in V2 sensitive to stereo disparity This neuron responds stronger when the left side is the owner of the borderline, defined by contrast (A, C) or by stereo disparity (E, F). Qiu & von der Heydt (2005), Neuron, 47, 155-166 Illusory figures /depth perception Mendola, J. D. et al. (1999) Journal of Neuroscience, 19, 8560-8572 human brain activity for stereoscopic depth and for illusory contours in overlapping brain areas Psychophysics of Kanizsa figures • Brightness nulling • Contour positioning • Depth nulling measuring brightness, contour and depth perception Previously used experimental techniques can now be used for larger set of variation figures to test different aspects of the model brightness nulling (Halpern, 1987, Spillman et al., 1984) contour positioning (Guttman & Kellman, 2004) depth nulling (Gregory & Harris, 1974,Whitmore et al., 1976) stereoscopic presentation L R adjusted gray scale (background=0) brightness nulling experiment figures contour positioning experiment distance from the contour (in pixels) outside 0 inside figures depth perception • adjustment task depth nulling (on-going project) Compare directly the perceived depth of different Kanizsa figure variations "in front“ “in-between” “behind” Application: Occlusion capture • Perceived surfaces create new, strong units (perceptual grouping, objectness) Some examples of other work in our lab • Overall ambitions: – To study Gestalt phenomena and to try to understand their underlying mechanisms by making use of all tools and techniques from modern vision science (multi-method approach) – To (re-)integrate the understanding of Gestalt phenomena into all that we know about vision and the visual brain • GestaltReVision program (funded by Flemish Government, METH/08/02) • www.gestaltrevision.be Another application of the DISC approach • Figure-ground multistability (perceptual switching) feedback influence to BOWN feedback figure side + ground side random numbers perception of face or vase image = alternation of border-ownership -+ +- feedback enhancement of a perception “It is a vase!” “It is even clearer!” feedback feedback - + - ++ multi-stable perception DFV 300 face 0 vase -300 1 200 iteration 400 600 800 1000 multi-stable perception DFV 300 continuous presentation face 0 vase -300 DFV intermittent presentation 300 face 0 vase -300 1 200 iteration 400 600 800 1000 gamma/beta-prime distribution disambiguation by Gestalt principle of “size” -10 0 (control) +10 +20 responses to disambiguated images -10 F=875 V=125 0 (control) F=480 V=520 +10 F=109 V=891 +20 F=0 V=1000 Some neuroimaging • fMRI decoding of neural representations – Jonas Kubilius et al. (submitted) – Lee de Wit et al. (in preparation) parts corner whole 11.4 8.4 -5.7 -4.1 V1 V2 V3 CS CS V1 V2 LO V3 pFs all > fixation objects > scrambled Diamonds are not forever What happens to local orientation signals (V1) and motion signals (V5) when percept changes from local to global? Diamonds are not forever What happens to local orientation signals (V1) and motion signals (V5) when percept changes from local to global? (real occlusion to disambiguate) A lot of psychophysics • On a wide variety of topics in mid-level vision, incl. – – – – – – – perceptual grouping figure-ground organization adaptation aftereffects masking biological motion haptic Gestalt formation … • Main focus: bridging gaps between levels – low-, mid-, and high-level – psychophysics, modeling and neural mechanisms Patient studies build-up paradigm, from random to perfectly structured – in children with autism (collaboration with Hull: Tjeerd Jellema & Hollie Burnett) • local – global • natural – manmade – in patients with brain deficits (collaboration with Birmingham: Glyn Humphreys) • different component processes: attention, grouping, figure-ground, shape, identity, semantic, … • neglect, agnosia, … Visual perception and visual arts • Announcement: conference in Brussels (23-24 November 2010) • Collaboration with contemporary, active, interested artists Anne-Mie Van Kerckhoven • best-known artist • works with a lot of different techniques (also digital) • important visual component to her work: perceptual organization 2D vs 3D contours vs surfaces figure-ground ambiguities (e.g., perceptual holes) – multiple depth layers – depth cues – … – – – – Effects of art expertise on individual scan paths • • the artist checking balance Effects of art expertise on individual scan paths • • the novice reading Effects of art expertise on individual scan paths • • the expert checking composition Summary • Kanizsa triangle has central place in vision science – crucial insights – generic value (general lessons to be drawn) – continuous source of inspiration • vision science should – be more interdisciplinary – continue to take phenomenology and psychophysics seriously – try to relate more to other visual disciplines (computer vision, arts) THANK YOU! MORE INFORMATION: WWW.GESTALTREVISION.BE [email protected]