Scientific and Large Data Visualization 25 October 2018 Visual Perception Massimiliano Corsini Visual Computing Lab, ISTI
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Optical Illusions and Effects on Clothing Design1
International Journal of Science Culture and Sport (IntJSCS) June 2015 : 3(2) ISSN : 2148-1148 Doi : 10.14486/IJSCS272 Optical Illusions and Effects on Clothing Design1 Saliha AĞAÇ*, Menekşe SAKARYA** * Associate Prof., Gazi University, Ankara, TURKEY, Email: [email protected] ** Niğde University, Niğde, TURKEY, Email: [email protected] Abstract “Visual perception” is in the first ranking between the types of perception. Gestalt Theory of the major psychological theories are used in how visual perception realizes and making sense of what is effective in this process. In perception stage brain takes into account not only stimulus from eyes but also expectations arising from previous experience and interpreted the stimulus which are not exist in the real world as if they were there. Misperception interpretations that brain revealed are called as “Perception Illusion” or “Optical Illusion” in psychology. Optical illusion formats come into existence due to factors such as brightness, contrast, motion, geometry and perspective, interpretation of three-dimensional images, cognitive status and color. Optical illusions have impacts of different disciplines within the study area on people. Among the most important types of known optical illusion are Oppel-Kundt, Curvature-Hering, Helzholtz Sqaure, Hermann Grid, Muller-Lyler, Ebbinghaus and Ponzo illusion etc. In fact, all the optical illusions are known to be used in numerous area with various techniques and different product groups like architecture, fine arts, textiles and fashion design from of old. In recent years, optical illusion types are frequently used especially within the field of fashion design in the clothing model, in style, silhouette and fabrics. The aim of this study is to examine the clothing design applications where optical illusion is used and works done in this subject. -
The Retina the Retina the Pigment Layer Contains Melanin That Prevents Light Reflection Throughout the Globe of the Eye
The Retina The retina The pigment layer contains melanin that prevents light reflection throughout the globe of the eye. It is also a store of Vitamin A. Rods and Cones Photoreceptors of the nervous system responsible for transforming light energy into the electrical energy of the nervous system. Bipolar cells Link between photoreceptors and ganglion cells. Horizontal cells Provide inhibition between bipolar cells. This is the mechanism of lateral inhibition which is important to edge detection and contrast enhancement. Amacrine cells Transmit excitatory signals from bipolar to ganglion cells. Thought to be important in signalling changes in light intensity. Neural circuitry About 125 rods and 5 cones converge on each optic nerve fibre. In the central portion of the fovea there are no rods. The ratio of cones to optic nerves in the fovea is one. This increases the visual acuity of the fovea. Rods and Cones Photosensitive substance in rods is called rhodopsin and in cones is called iodopsin. The Photochemistry of Vision Rhodopsin and Iodopsin Cis-retinal +Opsin Light sensitive Light Trans-retinal Opsin Light insensitive This is a reversible reaction Cis-retinal +Opsin Light sensitive Vitamin A In the presence of light, the rods and cones are hyperpolarized mv t Hyperpolarizing potential lasts for upto half a second, leading to the perception of fusion of flickering lights. Receptor potential – rod and cone potential Hyperpolarizing receptor potential caused by rhodopsin decomposition. Hyperpolarizing potential lasts for upto half a second, leading to the fusion of flickering lights. Light and dark adaptation in the visual system The eye is capable of vision in conditions of light that vary greatly in intensity The eye adapts dynamically to lighting conditions Light and Dark Adaptation We are able to see in light intensities that vary greatly. -
Informing Computer Vision with Optical Illusions
Informing Computer Vision with Optical Illusions Nasim Nematzadeh David M. W. Powers Trent Lewis College of Science and Engineering College of Science and Engineering College of Science and Engineering Flinders University Flinders University Flinders University Adelaide, Australia Adelaide, Australia Adelaide, Australia [email protected] [email protected] [email protected] Abstract— Illusions are fascinating and immediately catch the increasingly detailed biological characterization of both people's attention and interest, but they are also valuable in retinal and cortical cells over the last half a century (1960s- terms of giving us insights into human cognition and perception. 2010s), there remains considerable uncertainty, and even some A good theory of human perception should be able to explain the controversy, as to the nature and extent of the encoding of illusion, and a correct theory will actually give quantifiable visual information by the retina, and conversely of the results. We investigate here the efficiency of a computational subsequent processing and decoding in the cortex [6, 8]. filtering model utilised for modelling the lateral inhibition of retinal ganglion cells and their responses to a range of Geometric We explore the response of a simple bioplausible model of Illusions using isotropic Differences of Gaussian filters. This low-level vision on Geometric/Tile Illusions, reproducing the study explores the way in which illusions have been explained misperception of their geometry, that we reported for the Café and shows how a simple standard model of vision based on Wall and some Tile Illusions [2, 5] and here will report on a classical receptive fields can predict the existence of these range of Geometric illusions. -
A Neural Model of the Scintillating Grid Illusion: Disinhibi- Tion and Self-Inhibition in Early Vision
LETTER Communicated by Sidney Lehky A Neural Model of the Scintillating Grid Illusion: Disinhibi- tion and Self-Inhibition in Early Vision Yingwei Yu Downloaded from http://direct.mit.edu/neco/article-pdf/18/3/521/816498/neco.2006.18.3.521.pdf by guest on 24 September 2021 [email protected] Yoonsuck Choe [email protected] Department of Computer Science, Texas A&M University, College Station, Texas 77843-3112, U.S.A A stationary display of white discs positioned on intersecting gray bars on a dark background gives rise to a striking scintillating effect—the scin- tillating grid illusion. The spatial and temporal properties of the illusion are well known, but a neuronal-level explanation of the mechanism has not been fully investigated. Motivated by the neurophysiology of the Limulus retina, we propose disinhibition and self-inhibition as possible neural mechanisms that may give rise to the illusion. In this letter, a spa- tiotemporal model of the early visual pathway is derived that explicitly accounts for these two mechanisms. The model successfully predicted the change of strength in the illusion under various stimulus conditions, indicating that low-level mechanisms may well explain the scintillating effect in the illusion. 1 Introduction The scintillating grid illusion consists of bright discs superimposed on in- tersections of orthogonal gray bars on a dark background (see Figure 1A; Schrauf, Lingelbach, & Wist, 1997). In this illusion, illusory dark spots are perceived as scintillating within the white discs. Several important prop- erties of the illusion have been discovered and reported inrecent years. (1) The discs that are closer to a fixation show less scintillation (Schrauf et al., 1997), which might be due to the fact that receptive fields in the periphery are larger than those in the fovea. -
Color Appearance Models Second Edition
Color Appearance Models Second Edition Mark D. Fairchild Munsell Color Science Laboratory Rochester Institute of Technology, USA Color Appearance Models Wiley–IS&T Series in Imaging Science and Technology Series Editor: Michael A. Kriss Formerly of the Eastman Kodak Research Laboratories and the University of Rochester The Reproduction of Colour (6th Edition) R. W. G. Hunt Color Appearance Models (2nd Edition) Mark D. Fairchild Published in Association with the Society for Imaging Science and Technology Color Appearance Models Second Edition Mark D. Fairchild Munsell Color Science Laboratory Rochester Institute of Technology, USA Copyright © 2005 John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England Telephone (+44) 1243 779777 This book was previously publisher by Pearson Education, Inc Email (for orders and customer service enquiries): [email protected] Visit our Home Page on www.wileyeurope.com or www.wiley.com All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except under the terms of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London W1T 4LP, UK, without the permission in writing of the Publisher. Requests to the Publisher should be addressed to the Permissions Department, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, or emailed to [email protected], or faxed to (+44) 1243 770571. This publication is designed to offer Authors the opportunity to publish accurate and authoritative information in regard to the subject matter covered. -
Arxiv:1907.09019V2 [Cs.CV] 5 Aug 2019
Preprint IMAGENET-TRAINED DEEP NEURAL NETWORK EX- HIBITS ILLUSION-LIKE RESPONSE TO THE SCINTILLAT- ING GRID Eric Sun Ron Dekel Department of Physics Department of Neurobiology Department of Chemistry and Chemical Biology Weizmann Institute of Science Harvard University Rehovot, PA 7610001, Israel Cambridge, MA 02138, USA [email protected] eric [email protected] ABSTRACT Deep neural network (DNN) models for computer vision are now capable of human-level object recognition. Consequently, similarities in the performance and vulnerabilities of DNN and human vision are of great interest. Here we charac- terize the response of the VGG-19 DNN to images of the Scintillating Grid visual illusion, in which white dots are perceived to be partially black. We observed a significant deviation from the expected monotonic relation between VGG-19 rep- resentational dissimilarity and dot whiteness in the Scintillating Grid. That is, a linear increase in dot whiteness leads to a non-linear increase and then, remark- ably, a decrease (non-monotonicity) in representational dissimilarity. In control images, mostly monotonic relations between representational dissimilarity and dot whiteness were observed. Furthermore, the dot whiteness level correspond- ing to the maximal representational dissimilarity (i.e. onset of non-monotonic dissimilarity) matched closely with that corresponding to the onset of illusion per- ception in human observers. As such, the non-monotonic response in the DNN is a potential model correlate for human illusion perception. 1 INTRODUCTION Deep neural network (DNN) models are capable of besting human champions in chess [18] and Go [20] and reaching superhuman levels of accuracy in image classification and object recognition tasks [3, 11, 5, 18]. -
Sub-Riemannian Problems on 3D Lie Groups with Applications to Retinal
Sub-Riemannian Geometry in Image Processing and Modelling of Human Visual System Alexey Mashtakov Program Systems Institute of RAS Based on joint works with R. Duits, Yu. Sachkov, G. Citti, A. Sarti, A. Popov E. Bekkers, G. Sanguinetti, A. Ardentov, B. Franceschiello I. Beschastnyi, A. Ghosh and T.C.J. Dela Haije Scientific Heritage of Sergei A. Chaplygin Nonholonomic Mechanics, Vortex Structures and Hydrodynamics Cheboksary, Russia, 06.06.2019 SR geodesics on Lie Groups in Image Processing Crossing structures are Reconstruction of corrupted contours disentangled based on model of human vision Applications in medical image analysis SE(2) SO(3) SE(3) 2 Left-invariant sub-Riemannian structures 3 Optimal Control Problem: ODE-based Approach Optimality of Extremal Trajectories 5 Sub-Riemannian Wave Front 6 Sub-Riemannian Wave Front 7 Sub-Riemannian Wave Front 8 Self intersection of Sub-Riemannian Wave Front General case: astroidal shape of conjugate locus Special case with rotational symmetry A.Agrachev, Exponential mappings for contact sub-Riemannian structures. JDCS, 1996. 9 H. Chakir, J.P. Gauthier and I. Kupka, Small Subriemannian Balls on R3. JDCS, 1996. Sub-Riemannian Sphere 10 Sub-Riemannian Length Minimizers 11 Brain Inspired Methods in Computer Vision 12 12 Perception of Visual Information by Human Brain LGN (lateral geniculate nucleus) LGN V1 V1 13 Primary visual cortex A Model of the Primary Visual Cortex V1 Replicated from R. Duits, U. Boscain, F. Rossi, Y. Sachkov, 14 Association Fields via Cuspless Sub-Riemannian Geodesics in SE(2), JMIV, 2013. Cortical Based Model of Perceptual Completion 15 Detection of salient curves in images 16 16 Analysis of Images of the Retina Diabetic retinopathy --- one of the main causes of blindness. -
Book XVII License and the Law Editor: Ramon F
8 88 8 8nd 8 8888on.com 8888 Basic Photography in 180 Days Book XVII License and the Law Editor: Ramon F. aeroramon.com Contents 1 Day 1 1 1.1 Photography and the law ....................................... 1 1.1.1 United Kingdom ....................................... 2 1.1.2 United States ......................................... 6 1.1.3 Hong Kong .......................................... 8 1.1.4 Hungary ............................................ 8 1.1.5 Macau ............................................. 8 1.1.6 South Africa ......................................... 8 1.1.7 Sudan and South Sudan .................................... 9 1.1.8 India .............................................. 10 1.1.9 Iceland ............................................ 10 1.1.10 Spain ............................................. 10 1.1.11 Mexico ............................................ 10 1.1.12 See also ............................................ 10 1.1.13 Notes ............................................. 10 1.1.14 References .......................................... 10 1.1.15 External links ......................................... 12 2 Day 2 13 2.1 Observation .............................................. 13 2.1.1 Observation in science .................................... 14 2.1.2 Observational paradoxes ................................... 14 2.1.3 Biases ............................................. 15 2.1.4 Observations in philosophy .................................. 16 2.1.5 See also ........................................... -
Use of the Hermann Grid Illusion in the Measurement of Contrast Perception in Dyslexia
CORE Metadata, citation and similar papers at core.ac.uk Provided by Elsevier - Publisher Connector Vision Research 45 (2005) 1–8 www.elsevier.com/locate/visres Rapid communications Use of the Hermann grid illusion in the measurement of contrast perception in dyslexia James M. Gilchrist a,*, Barbara K. Pierscionek b, William M. Mann a a Department of Optometry, University of Bradford, Richmond Road, Bradford, BD7 1DP West Yorkshire, UK b School of Biomedical Sciences, University of Ulster, Cromore Road, Coleraine, BT52 1SA Northern Ireland, UK Received 12 March 2004; received in revised form 28 July 2004 Abstract We measured contrast thresholds for perception of the Hermann grid illusion, using different contrast polarities and mean lumi- nances, in dyslexics and non-dyslexics. Both groups of subjects gave significantly lower thresholds with grids having dark squares and light paths, but there was no significant threshold difference between groups. Perceived strength of illusion was also measured in grids at suprathreshold contrast levels. Dyslexics perceived the illusion to be significantly stronger than non-dyslexics when the grid had light paths and low luminance. Ó 2004 Elsevier Ltd. All rights reserved. Keywords: Dyslexia; Contrast perception; Hermann grid; Magnocellular 1. Introduction (Livingstone, Rosen, Drislane, & Galaburda, 1991) and psychophysical studies which indicate that some Dyslexia has been defined as a specific reading diffi- dyslexics suffer reduced sensitivity to contrast, flicker culty, inexplicable by any deficit in intelligence, learning and/or motion (Cornelissen, Richardson, Mason, & opportunity, motivation or sensory acuity (Critchley, Stein, 1995; Demb, Boynton, Best, & Heeger, 1998; 1970). The signs of dyslexia are varied and include Everatt, Bradshaw, & Hibbard, 1999; Lovegrove, abnormal phonological awareness, difficulties with writ- 1991; Lovegrove, Bowling, Badcock, & Blackwood, ing, spelling, auditory discrimination and visual process- 1980). -
Optical Illusion - Wikipedia, the Free Encyclopedia
Optical illusion - Wikipedia, the free encyclopedia Try Beta Log in / create account article discussion edit this page history [Hide] Wikipedia is there when you need it — now it needs you. $0.6M USD $7.5M USD Donate Now navigation Optical illusion Main page From Wikipedia, the free encyclopedia Contents Featured content This article is about visual perception. See Optical Illusion (album) for Current events information about the Time Requiem album. Random article An optical illusion (also called a visual illusion) is characterized by search visually perceived images that differ from objective reality. The information gathered by the eye is processed in the brain to give a percept that does not tally with a physical measurement of the stimulus source. There are three main types: literal optical illusions that create images that are interaction different from the objects that make them, physiological ones that are the An optical illusion. The square A About Wikipedia effects on the eyes and brain of excessive stimulation of a specific type is exactly the same shade of grey Community portal (brightness, tilt, color, movement), and cognitive illusions where the eye as square B. See Same color Recent changes and brain make unconscious inferences. illusion Contact Wikipedia Donate to Wikipedia Contents [hide] Help 1 Physiological illusions toolbox 2 Cognitive illusions 3 Explanation of cognitive illusions What links here 3.1 Perceptual organization Related changes 3.2 Depth and motion perception Upload file Special pages 3.3 Color and brightness -
Geometrical Illusions
Oxford Reference The Oxford Companion to Consciousness Edited by Tim Bayne, Axel Cleeremans, and Patrick Wilken Publisher: Oxford University Press Print Publication Date: 2009 Print ISBN-13: 9780198569510 Published online: 2010 Current Online Version: 2010 eISBN: 9780191727924 illusions Illusions confuse and bias the machinery in the brain that constructs our representations of the world, because they reveal a discrepancy between what we perceive and what is objectively out there in the world. But both illusions and accurate perceptions are governed by the same lawful perceptual processes. Despite the deceptive simplicity of illusions, there are no fully agreed theories about their causes. Illusions include geometrical illusions, in which angles, lengths, or shapes are misperceived; illusions of lightness, in which the context distorts the perceived lightness of objects; and illusions of representation, including puzzle pictures, ambiguous pictures, and impossible figures. 1. Geometrical illusions 2. Illusions of lightness 3. Illusions of representation 1. Geometrical illusions Figure I1 shows some illusory distortions in perceived angles, named after their discoverers; the Zollner, Hering and Poggendorff illusions, and Fraser's LIFE figure. Length illusions include the Müller–Lyer, the vertical–horizontal, and the Ponzo illusion. Shape illusions include Roger Shepard's tables and Kitaoka's bulge illusion. In the Zollner illusion, the long oblique lines are parallel, but they appear to be tilted away from the small fins that cross them. In the Hering illusion the verticals are parallel but appear to be bowed outward, again in a direction away from the inducing lines. In the Poggendorff illusion, the right‐hand oblique line looks as though it would pass above the left‐hand oblique if extended, although both are really exactly aligned. -
Grey Mono Family Overview
Grey Mono Family Overview Styles About the Font LL Grey is a sans serif born of a screen-friendly appearance. As Grey Mono Light French grotesque, with all the with his previous efforts LL Purple rude, cabaret-like stroke endings and LL Brown, Aurèle used a his- of the genre. First called AS Gold, toric predecessor for formal cues, Grey Mono Light Italic the typeface made its debut as but brought his signature surgi- part of Aurèle Sack’s diploma pro- cal precision to its rendering. The Grey Mono Book ject at ECAL in 2004. result is a pleasant widening of the Now distilled and extended into idiosyncratic proportions of 19th Grey Mono Book Mono a playful yet highly readable text century grotesques. font, LL Grey has a contemporary, Scripts Cyrillic кириллица File Formats Opentype CFF, Truetype, WOFF, WOFF2 Greek Ελληνικά Design Aurèle Sack (2020 – 2021) Contact General inquiries: Lineto GmbH Paneuropean abc абв αβγ [email protected] Lutherstrasse 32 CH-8004 Zürich Technical inquiries: Switzerland Separate [email protected] PDF Grey Sales & licensing inquiries: www.lineto.com [email protected] LL Grey Mono – Specimen 2 Lineto Type Foundry Glyph Overview Latin A B C D E F G H I J K L M N O P Q Cyrillic А а Б б В в Г г Ѓ ѓ Ґ ґ Д д Е е Ё R S T U V W X Y Z ё Ж ж З з И и Й й К к Ќ ќ Л л М м Н н О о П п Р р С с Т т У у Ў ў Ф Lowercase a b c d e f g h i j k l m n o p q ф Х х Ч ч Ц ц Ш ш Щ щ Џ џ Ъ ъ Ы ы r s ß t u v w x y z Ь ь Љ љ Њ њ Ѕ ѕ Є є Э э І і Ї ї Ј Proportional, ј Ћ ћ Ю ю Я я Ђ ђ Ѣ ѣ Ғ ғ Қ қ Ң ң Mono Figures 0 1 2 3 4 5 6 7 8 9 Ү ү Ұ ұ Ҳ ҳ Һ һ Ә ә Ө ө Ligatures fi fl Greek Α α Β β Γ γ Δ δ Ε ε Ζ ζ Η η Θ θ Ι ι Κ κ Extented Character set À à Á á Â â Ã ã Ä ä Å å Ā ā Ă ă Ą Λ λ Μ μ Ν ν Ξ ξ Ο ο Π π Ρ ρ Σ σ Τ τ ą Ǻ ǻ Ǽ ǽ Æ æ Ç ç Ć ć Ĉ ĉ Ċ ċ Č č Υ υ Φ φ Χ χ Ψ ψ Ω ω Σ ς Α ά Ε έ Η ή Ι ί Ď ď Đ đ È è É é Ê ê Ë ë Ē ē Ĕ ĕ Ė Ο ό Υ ύ Ω ώ Ϊ ϊ Ϋ ϋ Ϊ ΰ ė Ę ę Ě ě Ĝ ĝ Ğ ğ Ġ ġ Ģ ģ Ĥ ĥ Ħ ħ Punctuation ( .