Graphics and Perception. Carol O Sullivan

Size: px
Start display at page:

Download "Graphics and Perception. Carol O Sullivan"

Transcription

1 Graphics and Perception Carol O Sullivan Carol.OSullivan@cs.tcd.ie Trinity College Dublin

2 Outline Some basics Why perception is important For Modelling For Rendering For Animation Future research - multisensory perception and crowds

3

4

5

6

7

8 Why do we care? Rapid Developments in Graphics: Algorithmic: e.g., fluid, cloth, humans, etc Hardware: desktop PCs Low-end mobile devices, PDAs, cell phones More than just technical challenges: Fidelity? Plausibility? Presence? Perceptibility of errors? Evaluation? Metrics? Must consider human perception!

9 Modelling

10 Example Model simplification

11 How to measure fidelity? Watson et al Used experimental measures to evaluate simplification algorithms Naming times Ratings Forced-choice preferences Original (top), QSlim at 80% (middle) and Vclust 80% (bottom)

12 Perceptual simplification Users can guide the simplification process Pojar and Schmalstieg 2003 Kho and Garland 2003 Or salient features can be found automatically, or using an eye-tracker Howlett et al.2004 Lee et al.2005

13 We used an eye-tracker to determine the prominent features of models

14 Finding Salient Features We gathered information on where a participant was fixating while viewing a set of models.

15 We incorporated fixation data to produce a perceptual simplification metric Then asked people to name them, match them, and choose between them Evaluation

16 Rendering

17 Image Fidelity Fidelity to what? Stimulus Response Semantics How to assess fidelity? Metrics How to apply the notion to image production? Perceptually informed rendering To image reproduction? Tone mapping, contrast reduction, display device design How to evaluate perceptual methods?

18 Measuring Error Problem: Solution: Model the Human Visual System (HVS) VDP: Visible Differences VQEG/Modelfest SSIM: Structured Similarity

19 Visible Difference Predictors Probabilities of difference detection Two Images (e.g., frames of an animation) Daly/Myskowski

20 Example: Perceptual Rendering Can do user studies to find out what rendering components are perceptually important Then develop a metric to guide where to concentrate computationally expensive illumination components with respect to image quality. Ferwerda et al., 2004

21 High Dynamic Range image reproduction High Dynamic Range display device Seetzen et al present two designs for a HDR display device, based on the idea of a modulated backlight 1) LEDs array and 2) Digital Mirror Device A standard LCD device provides for color and further intensity modulation Limitations of the eye s ability to perceive local contrast (ratio of 150 to 1) are taken into account to determine: The minimum number of LEDs necessary in the array Adequate resolution and blur for the DMD projector The optimal number of bits necessary to drive each backlight

22 High Dynamic Range image reproduction Spatial kernel f Input Influence g in the intensity domain for the central pixel Weights Images courtesy of Fredo Durand and Julie Dorsey Output

23 Visual Attention and Tasks Attention is largely controlled by task: Scene rendered at low, high and selective resolution. Task allocated Difference in quality largely not noticed by participants Cater et al Selective Quality Image

24 Three varieties of realism Ferwerda 2003 Physical realism Same visual stimulation as scene Highly computationally expensive Photo-realism Same visual response as scene Takes observer s visual system into account Functional realism Same visual information as scene Information useful for completing a task

25 Human facial illustrations Gooch et al Images courtesy of Bruce Gooch

26 Human facial illustrations Gooch et al Presents a new technique for automatic NPR generation of faces from photos Photo illustration caricature Evaluates functional value of images Recognition task Learning task slower with photos Accuracy, speed

27 Duke et al Radar display Triangles Circles Rendering and affect Which is the threat? Invariant of a sharp shape invokes connotations of threat

28 Experiments Assessment of danger and safety Radar, door, house & trees Assessment of strength and weakness Radar, strongest man, weakest man Goal-directed interaction Paths, object selection

29 Results Demonstration of how rendering style can convey meaning and influence judgement Illustrate how semantics, affect and other high-level invariants need to be taken into account when analysing rendering methods, not just perceptual adequacy and realism.

30 Distance and Scale in VEs What affects perception of distance in VEs? Triangulated walking task Thompson et al Image Quality? Makes no difference Is it the HMD? Creem-Regehr et al No artificially generating these restrictions in the real world did not produce the same problems No need to see own body (see also Lok et al. 2003) However, some cues are important Hu et al Shadows and Interreflection affected performance in a placement task

31 Presence Slater et al Presence = the sense of being there. In the past, questionnaires and interviews were predominant Physiological measurements proposed as a viable alternative Shock of entering room with precipice induces physiological response Meehan et al Perhaps can also be used to measure and predict Breaks in Presence (BIP)

32 Animation

33 Measuring Error Reitsma and Pollard 03

34 Accuracy vs. Plausibility Chenney and Forsyth 00

35 Collision Handling

36 Collisions and Perception Evaluating the Visual Fidelity of Physically Based Animations. Collisions and Attention

37 Multisensory Perception: 1 The multisensory brain: Areas of brain not unisensory but active to other sensory information Growing body of evidence: Visual areas active during tactile perception Visual areas active during tactile object recognition Auditory areas of brain are active during lip reading (no sound)

38 Multisensory Perception: 2 The senses influence each other: You simply cannot predict perception by studying the senses in isolation

39 Perceptual metrics for crowds New metrics to evaluate human simulations, taking account of: Multisensory information: vision, motion and sound Crowd and scene scale Task based on psychophysical and neuroimaging results which will be used to: Devise new multisensory strategies for optimal LOD control Implement new error and comparison measurements for evaluation

40 State of the Art Dead Rising (Xbox 360), Capcom, 2006

41 State of the Art Madden NFL (Xbox 360), EA, 2006

42 State of the Art Project Gotham Racing (Xbox 360), Microsoft, 2005

43 State of the Art Assassin s Creed (Xbox 360), Ubisoft

44

45 Sound rendering for crowds Tsingos et al. - SIGGRAPH 2004 Wand and Straβer PBG 2005

icam06, HDR, and Image Appearance

icam06, HDR, and Image Appearance icam06, HDR, and Image Appearance Jiangtao Kuang, Mark D. Fairchild, Rochester Institute of Technology, Rochester, New York Abstract A new image appearance model, designated as icam06, has been developed

More information

PERCEPTUAL AND SOCIAL FIDELITY OF AVATARS AND AGENTS IN VIRTUAL REALITY. Benjamin R. Kunz, Ph.D. Department Of Psychology University Of Dayton

PERCEPTUAL AND SOCIAL FIDELITY OF AVATARS AND AGENTS IN VIRTUAL REALITY. Benjamin R. Kunz, Ph.D. Department Of Psychology University Of Dayton PERCEPTUAL AND SOCIAL FIDELITY OF AVATARS AND AGENTS IN VIRTUAL REALITY Benjamin R. Kunz, Ph.D. Department Of Psychology University Of Dayton MAICS 2016 Virtual Reality: A Powerful Medium Computer-generated

More information

MODIFICATION OF ADAPTIVE LOGARITHMIC METHOD FOR DISPLAYING HIGH CONTRAST SCENES BY AUTOMATING THE BIAS VALUE PARAMETER

MODIFICATION OF ADAPTIVE LOGARITHMIC METHOD FOR DISPLAYING HIGH CONTRAST SCENES BY AUTOMATING THE BIAS VALUE PARAMETER International Journal of Information Technology and Knowledge Management January-June 2012, Volume 5, No. 1, pp. 73-77 MODIFICATION OF ADAPTIVE LOGARITHMIC METHOD FOR DISPLAYING HIGH CONTRAST SCENES BY

More information

Photometric Image Processing for High Dynamic Range Displays. Matthew Trentacoste University of British Columbia

Photometric Image Processing for High Dynamic Range Displays. Matthew Trentacoste University of British Columbia Photometric Image Processing for High Dynamic Range Displays Matthew Trentacoste University of British Columbia Introduction High dynamic range (HDR) imaging Techniques that can store and manipulate images

More information

ISSN Vol.03,Issue.29 October-2014, Pages:

ISSN Vol.03,Issue.29 October-2014, Pages: ISSN 2319-8885 Vol.03,Issue.29 October-2014, Pages:5768-5772 www.ijsetr.com Quality Index Assessment for Toned Mapped Images Based on SSIM and NSS Approaches SAMEED SHAIK 1, M. CHAKRAPANI 2 1 PG Scholar,

More information

Psychophysics of night vision device halo

Psychophysics of night vision device halo University of Wollongong Research Online Faculty of Health and Behavioural Sciences - Papers (Archive) Faculty of Science, Medicine and Health 2009 Psychophysics of night vision device halo Robert S Allison

More information

Tone mapping. Digital Visual Effects, Spring 2009 Yung-Yu Chuang. with slides by Fredo Durand, and Alexei Efros

Tone mapping. Digital Visual Effects, Spring 2009 Yung-Yu Chuang. with slides by Fredo Durand, and Alexei Efros Tone mapping Digital Visual Effects, Spring 2009 Yung-Yu Chuang 2009/3/5 with slides by Fredo Durand, and Alexei Efros Tone mapping How should we map scene luminances (up to 1:100,000) 000) to display

More information

High dynamic range imaging and tonemapping

High dynamic range imaging and tonemapping High dynamic range imaging and tonemapping http://graphics.cs.cmu.edu/courses/15-463 15-463, 15-663, 15-862 Computational Photography Fall 2017, Lecture 12 Course announcements Homework 3 is out. - Due

More information

On Contrast Sensitivity in an Image Difference Model

On Contrast Sensitivity in an Image Difference Model On Contrast Sensitivity in an Image Difference Model Garrett M. Johnson and Mark D. Fairchild Munsell Color Science Laboratory, Center for Imaging Science Rochester Institute of Technology, Rochester New

More information

On Contrast Sensitivity in an Image Difference Model

On Contrast Sensitivity in an Image Difference Model On Contrast Sensitivity in an Image Difference Model Garrett M. Johnson and Mark D. Fairchild Munsell Color Science Laboratory, Center for Imaging Science Rochester Institute of Technology, Rochester New

More information

Computational Vision and Picture. Plan. Computational Vision and Picture. Distal vs. proximal stimulus. Vision as an inverse problem

Computational Vision and Picture. Plan. Computational Vision and Picture. Distal vs. proximal stimulus. Vision as an inverse problem Perceptual and Artistic Principles for Effective Computer Depiction Perceptual and Artistic Principles for Effective Computer Depiction Computational Vision and Picture Fredo Durand MIT- Lab for Computer

More information

Sound rendering in Interactive Multimodal Systems. Federico Avanzini

Sound rendering in Interactive Multimodal Systems. Federico Avanzini Sound rendering in Interactive Multimodal Systems Federico Avanzini Background Outline Ecological Acoustics Multimodal perception Auditory visual rendering of egocentric distance Binaural sound Auditory

More information

Unit IV: Sensation & Perception. Module 19 Vision Organization & Interpretation

Unit IV: Sensation & Perception. Module 19 Vision Organization & Interpretation Unit IV: Sensation & Perception Module 19 Vision Organization & Interpretation Visual Organization 19-1 Perceptual Organization 19-1 How do we form meaningful perceptions from sensory information? A group

More information

The Quality of Appearance

The Quality of Appearance ABSTRACT The Quality of Appearance Garrett M. Johnson Munsell Color Science Laboratory, Chester F. Carlson Center for Imaging Science Rochester Institute of Technology 14623-Rochester, NY (USA) Corresponding

More information

Visual computation of surface lightness: Local contrast vs. frames of reference

Visual computation of surface lightness: Local contrast vs. frames of reference 1 Visual computation of surface lightness: Local contrast vs. frames of reference Alan L. Gilchrist 1 & Ana Radonjic 2 1 Rutgers University, Newark, USA 2 University of Pennsylvania, Philadelphia, USA

More information

Digital Radiography using High Dynamic Range Technique

Digital Radiography using High Dynamic Range Technique Digital Radiography using High Dynamic Range Technique DAN CIURESCU 1, SORIN BARABAS 2, LIVIA SANGEORZAN 3, LIGIA NEICA 1 1 Department of Medicine, 2 Department of Materials Science, 3 Department of Computer

More information

PERCEIVING MOVEMENT. Ways to create movement

PERCEIVING MOVEMENT. Ways to create movement PERCEIVING MOVEMENT Ways to create movement Perception More than one ways to create the sense of movement Real movement is only one of them Slide 2 Important for survival Animals become still when they

More information

Multiscale model of Adaptation, Spatial Vision and Color Appearance

Multiscale model of Adaptation, Spatial Vision and Color Appearance Multiscale model of Adaptation, Spatial Vision and Color Appearance Sumanta N. Pattanaik 1 Mark D. Fairchild 2 James A. Ferwerda 1 Donald P. Greenberg 1 1 Program of Computer Graphics, Cornell University,

More information

VU Rendering SS Unit 8: Tone Reproduction

VU Rendering SS Unit 8: Tone Reproduction VU Rendering SS 2012 Unit 8: Tone Reproduction Overview 1. The Problem Image Synthesis Pipeline Different Image Types Human visual system Tone mapping Chromatic Adaptation 2. Tone Reproduction Linear methods

More information

Limitations of the Medium, compensation or accentuation

Limitations of the Medium, compensation or accentuation The Art and Science of Depiction Limitations of the Medium, compensation or accentuation Fredo Durand MIT- Lab for Computer Science Limitations of the medium The medium cannot usually produce the same

More information

Limitations of the medium

Limitations of the medium The Art and Science of Depiction Limitations of the Medium, compensation or accentuation Limitations of the medium The medium cannot usually produce the same stimulus Real scene (possibly imaginary) Stimulus

More information

The eye, displays and visual effects

The eye, displays and visual effects The eye, displays and visual effects Week 2 IAT 814 Lyn Bartram Visible light and surfaces Perception is about understanding patterns of light. Visible light constitutes a very small part of the electromagnetic

More information

Sensation & Perception

Sensation & Perception Sensation & Perception What is sensation & perception? Detection of emitted or reflected by Done by sense organs Process by which the and sensory information Done by the How does work? receptors detect

More information

Abdulmotaleb El Saddik Associate Professor Dr.-Ing., SMIEEE, P.Eng.

Abdulmotaleb El Saddik Associate Professor Dr.-Ing., SMIEEE, P.Eng. Abdulmotaleb El Saddik Associate Professor Dr.-Ing., SMIEEE, P.Eng. Multimedia Communications Research Laboratory University of Ottawa Ontario Research Network of E-Commerce www.mcrlab.uottawa.ca abed@mcrlab.uottawa.ca

More information

Realistic Image Synthesis

Realistic Image Synthesis Realistic Image Synthesis - HDR Capture & Tone Mapping - Philipp Slusallek Karol Myszkowski Gurprit Singh Karol Myszkowski LDR vs HDR Comparison Various Dynamic Ranges (1) 10-6 10-4 10-2 100 102 104 106

More information

Tonemapping and bilateral filtering

Tonemapping and bilateral filtering Tonemapping and bilateral filtering http://graphics.cs.cmu.edu/courses/15-463 15-463, 15-663, 15-862 Computational Photography Fall 2018, Lecture 6 Course announcements Homework 2 is out. - Due September

More information

Spatio-Temporal Retinex-like Envelope with Total Variation

Spatio-Temporal Retinex-like Envelope with Total Variation Spatio-Temporal Retinex-like Envelope with Total Variation Gabriele Simone and Ivar Farup Gjøvik University College; Gjøvik, Norway. Abstract Many algorithms for spatial color correction of digital images

More information

La photographie numérique. Frank NIELSEN Lundi 7 Juin 2010

La photographie numérique. Frank NIELSEN Lundi 7 Juin 2010 La photographie numérique Frank NIELSEN Lundi 7 Juin 2010 1 Le Monde digital Key benefits of the analog2digital paradigm shift? Dissociate contents from support : binarize Universal player (CPU, Turing

More information

Applications of Flash and No-Flash Image Pairs in Mobile Phone Photography

Applications of Flash and No-Flash Image Pairs in Mobile Phone Photography Applications of Flash and No-Flash Image Pairs in Mobile Phone Photography Xi Luo Stanford University 450 Serra Mall, Stanford, CA 94305 xluo2@stanford.edu Abstract The project explores various application

More information

Regan Mandryk. Depth and Space Perception

Regan Mandryk. Depth and Space Perception Depth and Space Perception Regan Mandryk Disclaimer Many of these slides include animated gifs or movies that may not be viewed on your computer system. They should run on the latest downloads of Quick

More information

Computational Photography

Computational Photography Computational photography Computational Photography Digital Visual Effects Yung-Yu Chuang wikipedia: Computational photography h refers broadly to computational imaging techniques that enhance or extend

More information

Salient features make a search easy

Salient features make a search easy Chapter General discussion This thesis examined various aspects of haptic search. It consisted of three parts. In the first part, the saliency of movability and compliance were investigated. In the second

More information

A Vestibular Sensation: Probabilistic Approaches to Spatial Perception (II) Presented by Shunan Zhang

A Vestibular Sensation: Probabilistic Approaches to Spatial Perception (II) Presented by Shunan Zhang A Vestibular Sensation: Probabilistic Approaches to Spatial Perception (II) Presented by Shunan Zhang Vestibular Responses in Dorsal Visual Stream and Their Role in Heading Perception Recent experiments

More information

Perception. Read: AIMA Chapter 24 & Chapter HW#8 due today. Vision

Perception. Read: AIMA Chapter 24 & Chapter HW#8 due today. Vision 11-25-2013 Perception Vision Read: AIMA Chapter 24 & Chapter 25.3 HW#8 due today visual aural haptic & tactile vestibular (balance: equilibrium, acceleration, and orientation wrt gravity) olfactory taste

More information

Introduction to Visual Perception

Introduction to Visual Perception The Art and Science of Depiction Introduction to Visual Perception Fredo Durand and Julie Dorsey MIT- Lab for Computer Science Vision is not straightforward The complexity of the problem was completely

More information

Perceptual and Artistic Principles for Effective Computer Depiction. Gaze Movement & Focal Points

Perceptual and Artistic Principles for Effective Computer Depiction. Gaze Movement & Focal Points Perceptual and Artistic Principles for Effective Computer Depiction Perceptual and Artistic Principles for Effective Computer Depiction Perceptual and Artistic Principles for Effective Computer Depiction

More information

Crossmodal Attention & Multisensory Integration: Implications for Multimodal Interface Design. In the Realm of the Senses

Crossmodal Attention & Multisensory Integration: Implications for Multimodal Interface Design. In the Realm of the Senses Crossmodal Attention & Multisensory Integration: Implications for Multimodal Interface Design Charles Spence Department of Experimental Psychology, Oxford University In the Realm of the Senses Wickens

More information

Embodiment illusions via multisensory integration

Embodiment illusions via multisensory integration Embodiment illusions via multisensory integration COGS160: sensory systems and neural coding presenter: Pradeep Shenoy 1 The illusory hand Botvinnik, Science 2004 2 2 This hand is my hand An illusion of

More information

Visual Perception. human perception display devices. CS Visual Perception

Visual Perception. human perception display devices. CS Visual Perception Visual Perception human perception display devices 1 Reference Chapters 4, 5 Designing with the Mind in Mind by Jeff Johnson 2 Visual Perception Most user interfaces are visual in nature. So, it is important

More information

E90 Project Proposal. 6 December 2006 Paul Azunre Thomas Murray David Wright

E90 Project Proposal. 6 December 2006 Paul Azunre Thomas Murray David Wright E90 Project Proposal 6 December 2006 Paul Azunre Thomas Murray David Wright Table of Contents Abstract 3 Introduction..4 Technical Discussion...4 Tracking Input..4 Haptic Feedack.6 Project Implementation....7

More information

Realtime 3D Computer Graphics Virtual Reality

Realtime 3D Computer Graphics Virtual Reality Realtime 3D Computer Graphics Virtual Reality Marc Erich Latoschik AI & VR Lab Artificial Intelligence Group University of Bielefeld Virtual Reality (or VR for short) Virtual Reality (or VR for short)

More information

High dynamic range and tone mapping Advanced Graphics

High dynamic range and tone mapping Advanced Graphics High dynamic range and tone mapping Advanced Graphics Rafał Mantiuk Computer Laboratory, University of Cambridge Cornell Box: need for tone-mapping in graphics Rendering Photograph 2 Real-world scenes

More information

Photometric image processing for high dynamic range displays

Photometric image processing for high dynamic range displays J. Vis. Commun. Image R. 18 (2007) 439 451 www.elsevier.com/locate/jvci Photometric image processing for high dynamic range displays Matthew Trentacoste a, *, Wolfgang Heidrich a, Lorne Whitehead a, Helge

More information

CSE 165: 3D User Interaction. Lecture #14: 3D UI Design

CSE 165: 3D User Interaction. Lecture #14: 3D UI Design CSE 165: 3D User Interaction Lecture #14: 3D UI Design 2 Announcements Homework 3 due tomorrow 2pm Monday: midterm discussion Next Thursday: midterm exam 3D UI Design Strategies 3 4 Thus far 3DUI hardware

More information

Objective and subjective evaluations of some recent image compression algorithms

Objective and subjective evaluations of some recent image compression algorithms 31st Picture Coding Symposium May 31 June 3, 2015, Cairns, Australia Objective and subjective evaluations of some recent image compression algorithms Marco Bernando, Tim Bruylants, Touradj Ebrahimi, Karel

More information

Fixing the Gaussian Blur : the Bilateral Filter

Fixing the Gaussian Blur : the Bilateral Filter Fixing the Gaussian Blur : the Bilateral Filter Lecturer: Jianbing Shen Email : shenjianbing@bit.edu.cnedu Office room : 841 http://cs.bit.edu.cn/shenjianbing cn/shenjianbing Note: contents copied from

More information

LIGHTING IN REAL AND PICTORIAL SPACES

LIGHTING IN REAL AND PICTORIAL SPACES B. Dave, A. I. Li, N. Gu, H.-J. Park (eds.), New Frontiers: Proceedings of the 15th International Conference on Computer-Aided Architectural Design Research in Asia CAADRIA 2010, 501 510. 2010, Association

More information

Visibility of Uncorrelated Image Noise

Visibility of Uncorrelated Image Noise Visibility of Uncorrelated Image Noise Jiajing Xu a, Reno Bowen b, Jing Wang c, and Joyce Farrell a a Dept. of Electrical Engineering, Stanford University, Stanford, CA. 94305 U.S.A. b Dept. of Psychology,

More information

Issue Date: Volume: 24 Issue: 10 (October 2001)

Issue Date: Volume: 24 Issue: 10 (October 2001) Advanced Computer Graphics World - Issue Articles You are here: Computer Graphics World : CGW : Articles : Seeing with the Mind's Eye Issue Date: Volume: 24 Issue: 10 (October 2001) Seeing with the Mind's

More information

Human Vision. Human Vision - Perception

Human Vision. Human Vision - Perception 1 Human Vision SPATIAL ORIENTATION IN FLIGHT 2 Limitations of the Senses Visual Sense Nonvisual Senses SPATIAL ORIENTATION IN FLIGHT 3 Limitations of the Senses Visual Sense Nonvisual Senses Sluggish source

More information

GAZE contingent display techniques attempt

GAZE contingent display techniques attempt EE367, WINTER 2017 1 Gaze Contingent Foveated Rendering Sanyam Mehra, Varsha Sankar {sanyam, svarsha}@stanford.edu Abstract The aim of this paper is to present experimental results for gaze contingent

More information

What is Color Gamut? Public Information Display. How do we see color and why it matters for your PID options?

What is Color Gamut? Public Information Display. How do we see color and why it matters for your PID options? What is Color Gamut? How do we see color and why it matters for your PID options? One of the buzzwords at CES 2017 was broader color gamut. In this whitepaper, our experts unwrap this term to help you

More information

MEASURING IMAGES: DIFFERENCES, QUALITY AND APPEARANCE

MEASURING IMAGES: DIFFERENCES, QUALITY AND APPEARANCE MEASURING IMAGES: DIFFERENCES, QUALITY AND APPEARANCE Garrett M. Johnson M.S. Color Science (998) A dissertation submitted in partial fulfillment of the requirements for the degree of Ph.D. in the Chester

More information

Output Devices - Visual

Output Devices - Visual IMGD 5100: Immersive HCI Output Devices - Visual Robert W. Lindeman Associate Professor Department of Computer Science Worcester Polytechnic Institute gogo@wpi.edu Overview Here we are concerned with technology

More information

25/02/2017. C = L max L min. L max C 10. = log 10. = log 2 C 2. Cornell Box: need for tone-mapping in graphics. Dynamic range

25/02/2017. C = L max L min. L max C 10. = log 10. = log 2 C 2. Cornell Box: need for tone-mapping in graphics. Dynamic range Cornell Box: need for tone-mapping in graphics High dynamic range and tone mapping Advanced Graphics Rafał Mantiuk Computer Laboratory, University of Cambridge Rendering Photograph 2 Real-world scenes

More information

Optical Marionette: Graphical Manipulation of Human s Walking Direction

Optical Marionette: Graphical Manipulation of Human s Walking Direction Optical Marionette: Graphical Manipulation of Human s Walking Direction Akira Ishii, Ippei Suzuki, Shinji Sakamoto, Keita Kanai Kazuki Takazawa, Hiraku Doi, Yoichi Ochiai (Digital Nature Group, University

More information

Cognition and Perception

Cognition and Perception Cognition and Perception 2/10/10 4:25 PM Scribe: Katy Ionis Today s Topics Visual processing in the brain Visual illusions Graphical perceptions vs. graphical cognition Preattentive features for design

More information

High-Dynamic-Range (HDR) Vision

High-Dynamic-Range (HDR) Vision B. Hoefflinger (Ed.) High-Dynamic-Range (HDR) Vision Microelectronics, Image Processing, Computer Graphics With 172 Figures Sprin ger Contents 1 The Eye and High-Dynamic-Range Vision Bernd Hoefflinger

More information

Gaze Direction in Virtual Reality Using Illumination Modulation and Sound

Gaze Direction in Virtual Reality Using Illumination Modulation and Sound Gaze Direction in Virtual Reality Using Illumination Modulation and Sound Eli Ben-Joseph and Eric Greenstein Stanford EE 267, Virtual Reality, Course Report, Instructors: Gordon Wetzstein and Robert Konrad

More information

Plan. Vision Solves Problems. Distal vs. proximal stimulus. Vision as an inverse problem. Unconscious inference (Helmholtz)

Plan. Vision Solves Problems. Distal vs. proximal stimulus. Vision as an inverse problem. Unconscious inference (Helmholtz) The Art and Science of Depiction Vision Solves Problems Plan Vision as an cognitive process Computational theory of vision Constancy, invariants Fredo Durand MIT- Lab for Computer Science Intro to Visual

More information

MULTI-LAYERED HYBRID ARCHITECTURE TO SOLVE COMPLEX TASKS OF AN AUTONOMOUS MOBILE ROBOT

MULTI-LAYERED HYBRID ARCHITECTURE TO SOLVE COMPLEX TASKS OF AN AUTONOMOUS MOBILE ROBOT MULTI-LAYERED HYBRID ARCHITECTURE TO SOLVE COMPLEX TASKS OF AN AUTONOMOUS MOBILE ROBOT F. TIECHE, C. FACCHINETTI and H. HUGLI Institute of Microtechnology, University of Neuchâtel, Rue de Tivoli 28, CH-2003

More information

Perception in Immersive Environments

Perception in Immersive Environments Perception in Immersive Environments Scott Kuhl Department of Computer Science Augsburg College scott@kuhlweb.com Abstract Immersive environment (virtual reality) systems provide a unique way for researchers

More information

ABSTRACT. Keywords: color appearance, image appearance, image quality, vision modeling, image rendering

ABSTRACT. Keywords: color appearance, image appearance, image quality, vision modeling, image rendering Image appearance modeling Mark D. Fairchild and Garrett M. Johnson * Munsell Color Science Laboratory, Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA

More information

CSE 332/564: Visualization. Fundamentals of Color. Perception of Light Intensity. Computer Science Department Stony Brook University

CSE 332/564: Visualization. Fundamentals of Color. Perception of Light Intensity. Computer Science Department Stony Brook University Perception of Light Intensity CSE 332/564: Visualization Fundamentals of Color Klaus Mueller Computer Science Department Stony Brook University How Many Intensity Levels Do We Need? Dynamic Intensity Range

More information

ABSTRACT. Keywords: Color image differences, image appearance, image quality, vision modeling 1. INTRODUCTION

ABSTRACT. Keywords: Color image differences, image appearance, image quality, vision modeling 1. INTRODUCTION Measuring Images: Differences, Quality, and Appearance Garrett M. Johnson * and Mark D. Fairchild Munsell Color Science Laboratory, Chester F. Carlson Center for Imaging Science, Rochester Institute of

More information

Why interest in visual perception?

Why interest in visual perception? Raffaella Folgieri Digital Information & Communication Departiment Constancy factors in visual perception 26/11/2010, Gjovik, Norway Why interest in visual perception? to investigate main factors in VR

More information

Non-Photorealistic Rendering

Non-Photorealistic Rendering CSCI 420 Computer Graphics Lecture 24 Non-Photorealistic Rendering Jernej Barbic University of Southern California Pen-and-ink Illustrations Painterly Rendering Cartoon Shading Technical Illustrations

More information

Vision V Perceiving Movement

Vision V Perceiving Movement Vision V Perceiving Movement Overview of Topics Chapter 8 in Goldstein (chp. 9 in 7th ed.) Movement is tied up with all other aspects of vision (colour, depth, shape perception...) Differentiating self-motion

More information

A Handheld Image Analysis System for Portable and Objective Print Quality Analysis

A Handheld Image Analysis System for Portable and Objective Print Quality Analysis A Handheld Image Analysis System for Portable and Objective Print Quality Analysis Ming-Kai Tse Quality Engineering Associates (QEA), Inc. Contact information as of 2010: 755 Middlesex Turnpike, Unit 3

More information

Vision V Perceiving Movement

Vision V Perceiving Movement Vision V Perceiving Movement Overview of Topics Chapter 8 in Goldstein (chp. 9 in 7th ed.) Movement is tied up with all other aspects of vision (colour, depth, shape perception...) Differentiating self-motion

More information

The luminance of pure black: exploring the effect of surround in the context of electronic displays

The luminance of pure black: exploring the effect of surround in the context of electronic displays The luminance of pure black: exploring the effect of surround in the context of electronic displays Rafa l K. Mantiuk a,b, Scott Daly b and Louis Kerofsky b a Bangor University, School of Computer Science,

More information

Perception. The process of organizing and interpreting information, enabling us to recognize meaningful objects and events.

Perception. The process of organizing and interpreting information, enabling us to recognize meaningful objects and events. Perception The process of organizing and interpreting information, enabling us to recognize meaningful objects and events. Perceptual Ideas Perception Selective Attention: focus of conscious

More information

Non-Photorealistic Rendering

Non-Photorealistic Rendering CSCI 480 Computer Graphics Lecture 23 Non-Photorealistic Rendering April 16, 2012 Jernej Barbic University of Southern California http://www-bcf.usc.edu/~jbarbic/cs480-s12/ Pen-and-ink Illustrations Painterly

More information

Compression Method for High Dynamic Range Intensity to Improve SAR Image Visibility

Compression Method for High Dynamic Range Intensity to Improve SAR Image Visibility Compression Method for High Dynamic Range Intensity to Improve SAR Image Visibility Satoshi Hisanaga, Koji Wakimoto and Koji Okamura Abstract It is possible to interpret the shape of buildings based on

More information

Contours, Saliency & Tone Mapping. Donald P. Greenberg Visual Imaging in the Electronic Age Lecture 21 November 3, 2016

Contours, Saliency & Tone Mapping. Donald P. Greenberg Visual Imaging in the Electronic Age Lecture 21 November 3, 2016 Contours, Saliency & Tone Mapping Donald P. Greenberg Visual Imaging in the Electronic Age Lecture 21 November 3, 2016 Foveal Resolution Resolution Limit for Reading at 18" The triangle subtended by a

More information

Chapter 3: Psychophysical studies of visual object recognition

Chapter 3: Psychophysical studies of visual object recognition BEWARE: These are preliminary notes. In the future, they will become part of a textbook on Visual Object Recognition. Chapter 3: Psychophysical studies of visual object recognition We want to understand

More information

DESIGNING AND CONDUCTING USER STUDIES

DESIGNING AND CONDUCTING USER STUDIES DESIGNING AND CONDUCTING USER STUDIES MODULE 4: When and how to apply Eye Tracking Kristien Ooms Kristien.ooms@UGent.be EYE TRACKING APPLICATION DOMAINS Usability research Software, websites, etc. Virtual

More information

Evaluating Context-Aware Saliency Detection Method

Evaluating Context-Aware Saliency Detection Method Evaluating Context-Aware Saliency Detection Method Christine Sawyer Santa Barbara City College Computer Science & Mechanical Engineering Funding: Office of Naval Research Defense University Research Instrumentation

More information

Color appearance in image displays

Color appearance in image displays Rochester Institute of Technology RIT Scholar Works Presentations and other scholarship 1-18-25 Color appearance in image displays Mark Fairchild Follow this and additional works at: http://scholarworks.rit.edu/other

More information

Eccentricity Effect of Motion Silencing on Naturalistic Videos Lark Kwon Choi*, Lawrence K. Cormack, and Alan C. Bovik

Eccentricity Effect of Motion Silencing on Naturalistic Videos Lark Kwon Choi*, Lawrence K. Cormack, and Alan C. Bovik Eccentricity Effect of Motion Silencing on Naturalistic Videos Lark Kwon Choi*, Lawrence K. Cormack, and Alan C. Bovik Dec. 6, 206 Outline Introduction Background Visual Masking and Motion Silencing Eccentricity

More information

A new algorithm for calculating perceived colour difference of images

A new algorithm for calculating perceived colour difference of images Loughborough University Institutional Repository A new algorithm for calculating perceived colour difference of images This item was submitted to Loughborough University's Institutional Repository by the/an

More information

Review Paper on. Quantitative Image Quality Assessment Medical Ultrasound Images

Review Paper on. Quantitative Image Quality Assessment Medical Ultrasound Images Review Paper on Quantitative Image Quality Assessment Medical Ultrasound Images Kashyap Swathi Rangaraju, R V College of Engineering, Bangalore, Dr. Kishor Kumar, GE Healthcare, Bangalore C H Renumadhavi

More information

AUGMENTED VIRTUAL REALITY APPLICATIONS IN MANUFACTURING

AUGMENTED VIRTUAL REALITY APPLICATIONS IN MANUFACTURING 6 th INTERNATIONAL MULTIDISCIPLINARY CONFERENCE AUGMENTED VIRTUAL REALITY APPLICATIONS IN MANUFACTURING Peter Brázda, Jozef Novák-Marcinčin, Faculty of Manufacturing Technologies, TU Košice Bayerova 1,

More information

icam06: A refined image appearance model for HDR image rendering

icam06: A refined image appearance model for HDR image rendering J. Vis. Commun. Image R. 8 () 46 44 www.elsevier.com/locate/jvci icam6: A refined image appearance model for HDR image rendering Jiangtao Kuang *, Garrett M. Johnson, Mark D. Fairchild Munsell Color Science

More information

Tone mapping. Tone mapping The ultimate goal is a visual match. Eye is not a photometer! How should we map scene luminances (up to

Tone mapping. Tone mapping The ultimate goal is a visual match. Eye is not a photometer! How should we map scene luminances (up to Tone mapping Tone mapping Digital Visual Effects Yung-Yu Chuang How should we map scene luminances up to 1:100000 000 to displa luminances onl around 1:100 to produce a satisfactor image? Real world radiance

More information

Chapter 1 The Military Operational Environment... 3

Chapter 1 The Military Operational Environment... 3 CONTENTS Contributors... ii Foreword... xiii Preface... xv Part One: Identifying the Challenge Chapter 1 The Military Operational Environment... 3 Keith L. Hiatt and Clarence E. Rash Current and Changing

More information

Extended Dynamic Range Imaging: A Spatial Down-Sampling Approach

Extended Dynamic Range Imaging: A Spatial Down-Sampling Approach 2014 IEEE International Conference on Systems, Man, and Cybernetics October 5-8, 2014, San Diego, CA, USA Extended Dynamic Range Imaging: A Spatial Down-Sampling Approach Huei-Yung Lin and Jui-Wen Huang

More information

Implementation of Adaptive Coded Aperture Imaging using a Digital Micro-Mirror Device for Defocus Deblurring

Implementation of Adaptive Coded Aperture Imaging using a Digital Micro-Mirror Device for Defocus Deblurring Implementation of Adaptive Coded Aperture Imaging using a Digital Micro-Mirror Device for Defocus Deblurring Ashill Chiranjan and Bernardt Duvenhage Defence, Peace, Safety and Security Council for Scientific

More information

Effect of Scenario on Perceptual Sensitivity to Errors in Animation

Effect of Scenario on Perceptual Sensitivity to Errors in Animation Effect of Scenario on Perceptual Sensitivity to Errors in Animation Paul S. A. Reitsma Carol O Sullivan Trinity College Dublin Abstract A deeper understanding of what makes animation perceptually plausible

More information

Object Perception. 23 August PSY Object & Scene 1

Object Perception. 23 August PSY Object & Scene 1 Object Perception Perceiving an object involves many cognitive processes, including recognition (memory), attention, learning, expertise. The first step is feature extraction, the second is feature grouping

More information

Seeing and Perception. External features of the Eye

Seeing and Perception. External features of the Eye Seeing and Perception Deceives the Eye This is Madness D R Campbell School of Computing University of Paisley 1 External features of the Eye The circular opening of the iris muscles forms the pupil, which

More information

Virtual Reality I. Visual Imaging in the Electronic Age. Donald P. Greenberg November 9, 2017 Lecture #21

Virtual Reality I. Visual Imaging in the Electronic Age. Donald P. Greenberg November 9, 2017 Lecture #21 Virtual Reality I Visual Imaging in the Electronic Age Donald P. Greenberg November 9, 2017 Lecture #21 1968: Ivan Sutherland 1990s: HMDs, Henry Fuchs 2013: Google Glass History of Virtual Reality 2016:

More information

Part I Introduction to the Human Visual System (HVS)

Part I Introduction to the Human Visual System (HVS) Contents List of Figures..................................................... List of Tables...................................................... List of Listings.....................................................

More information

Fast Bilateral Filtering for the Display of High-Dynamic-Range Images

Fast Bilateral Filtering for the Display of High-Dynamic-Range Images Fast Bilateral Filtering for the Display of High-Dynamic-Range Images Frédo Durand & Julie Dorsey Laboratory for Computer Science Massachusetts Institute of Technology Contributions Contrast reduction

More information

A New Metric for Color Halftone Visibility

A New Metric for Color Halftone Visibility A New Metric for Color Halftone Visibility Qing Yu and Kevin J. Parker, Robert Buckley* and Victor Klassen* Dept. of Electrical Engineering, University of Rochester, Rochester, NY *Corporate Research &

More information

Inversion improves the recognition of facial expression in thatcherized images

Inversion improves the recognition of facial expression in thatcherized images Perception, 214, volume 43, pages 715 73 doi:1.168/p7755 Inversion improves the recognition of facial expression in thatcherized images Lilia Psalta, Timothy J Andrews Department of Psychology and York

More information

Modeling and Synthesis of Aperture Effects in Cameras

Modeling and Synthesis of Aperture Effects in Cameras Modeling and Synthesis of Aperture Effects in Cameras Douglas Lanman, Ramesh Raskar, and Gabriel Taubin Computational Aesthetics 2008 20 June, 2008 1 Outline Introduction and Related Work Modeling Vignetting

More information

The IQ3 100MP Trichromatic. The science of color

The IQ3 100MP Trichromatic. The science of color The IQ3 100MP Trichromatic The science of color Our color philosophy Phase One s approach Phase One s knowledge of sensors comes from what we ve learned by supporting more than 400 different types of camera

More information

Virtual Environments. Ruth Aylett

Virtual Environments. Ruth Aylett Virtual Environments Ruth Aylett Aims of the course 1. To demonstrate a critical understanding of modern VE systems, evaluating the strengths and weaknesses of the current VR technologies 2. To be able

More information

BODILY NON-VERBAL INTERACTION WITH VIRTUAL CHARACTERS

BODILY NON-VERBAL INTERACTION WITH VIRTUAL CHARACTERS KEER2010, PARIS MARCH 2-4 2010 INTERNATIONAL CONFERENCE ON KANSEI ENGINEERING AND EMOTION RESEARCH 2010 BODILY NON-VERBAL INTERACTION WITH VIRTUAL CHARACTERS Marco GILLIES *a a Department of Computing,

More information