Literature DB >> 20438232

Surface construction by a 2-D differentiation-integration process: a neurocomputational model for perceived border ownership, depth, and lightness in Kanizsa figures.

Naoki Kogo1, Christoph Strecha, Luc Van Gool, Johan Wagemans.   

Abstract

Human visual perception is a fundamentally relational process: Lightness perception depends on luminance ratios, and depth perception depends on occlusion (difference of depth) cues. Neurons in low-level visual cortex are sensitive to the difference (but not the value itself) of signals, and these differences have to be used to reconstruct the input. This process can be regarded as a 2-dimensional differentiation and integration process: First, differentiated signals for depth and lightness are created at an earlier stage of visual processing and then 2-dimensionally integrated at a later stage to construct surfaces. The subjective filling in of physically missing parts of input images (completion) can be explained as a property that emerges from this surface construction process. This approach is implemented in a computational model, called DISC (Differentiation-Integration for Surface Completion). In the DISC model, border ownership (the depth order at borderlines) is computed based on local occlusion cues (L- and T-junctions) and the distribution of borderlines. Two-dimensional integration is then applied to construct surfaces in the depth domain, and lightness values are in turn modified by these depth measurements. Illusory percepts emerge through the surface-construction process with the development of illusory border ownership and through the interaction between depth and lightness perception. The DISC model not only produces a central surface with the correctly modified lightness values of the original Kanizsa figure but also responds to variations of this figure such that it can distinguish between illusory and nonillusory configurations in a manner that is consistent with human perception. PsycINFO Database Record (c) 2010 APA, all rights reserved.

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Year:  2010        PMID: 20438232     DOI: 10.1037/a0019076

Source DB:  PubMed          Journal:  Psychol Rev        ISSN: 0033-295X            Impact factor:   8.934


  13 in total

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2.  Receptive field focus of visual area V4 neurons determines responses to illusory surfaces.

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Review 4.  Forms of prediction in the nervous system.

Authors:  Christoph Teufel; Paul C Fletcher
Journal:  Nat Rev Neurosci       Date:  2020-03-10       Impact factor: 34.870

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Authors:  Johan Wagemans
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6.  Kanizsa illusory contours appearing in the plasmodium pattern of Physarum polycephalum.

Authors:  Iori Tani; Masaki Yamachiyo; Tomohiro Shirakawa; Yukio-Pegio Gunji
Journal:  Front Cell Infect Microbiol       Date:  2014-02-28       Impact factor: 5.293

7.  A conceptual framework of computations in mid-level vision.

Authors:  Jonas Kubilius; Johan Wagemans; Hans P Op de Beeck
Journal:  Front Comput Neurosci       Date:  2014-12-12       Impact factor: 2.380

8.  Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception.

Authors:  Aaron M Clarke; Michael H Herzog; Gregory Francis
Journal:  Front Psychol       Date:  2014-10-21

9.  Volume Completion Between Contour Fragments at Discrete Depths.

Authors:  Peter Ulric Tse
Journal:  Iperception       Date:  2017-12-21

10.  Induction of Kanizsa Contours Requires Awareness of the Inducing Context.

Authors:  Theodora Banica; D Samuel Schwarzkopf
Journal:  PLoS One       Date:  2016-08-12       Impact factor: 3.240

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