The Human Visual System!
|
|
|
- Lorena Bell
- 6 years ago
- Views:
Transcription
1 ! The Human Visual System! Gordon Wetzstein! Stanford University! EE 267 Virtual Reality! Lecture 5! stanford.edu/class/ee267/!!
2 nautilus eye, wikipedia!
3 Dawkins, Climbing Mount Improbable,! Norton & Company, 1997!
4 reptile eye,
5 wikipedia! Evolution of the Eye! owl,
6 pigeon,
7 jumping spider, wikipedia!
8 national geographics!
9 Lecture Overview! visual acuity: 20/20 is ~1 arc min! visual acuity varies over retina: can exploit via foveated rendering! field of view: ~190 monocular, ~120 binocular, ~135 vertical! temporal resolution: ~60 Hz (depends on contrast, luminance)! depth cues in 3D displays: disparity, vergence, accommodation, blur,! accommodation range: ~8cm to, degrades with age!
10 Overview! wikipedia! sensors! low-level processing! network! compute! high-level processing!
11 Overview! dorsal stream: spatial awareness! wikipedia! primary visual cortex! ventral stream:! recognition, object identification!
12 Overview! van der Helm!
13 Anatomy of the Human Eye!
14 The Retina! Roorda & Williams, 1999, Nature! 5 arcmin visual angle! photoreceptors: 3 types of cones (color vision), rods (luminance only, night vision)!
15 The Retina!
16 Color Perception!
17 reddit.com! Color Perception - Sensitivity of Cones!
18 Ruch & Fulton, 1960! Visual Field / Field of View! monocular visual field! binocular visual field!
19 Immersive VR How Important is the FOV?!
20 Visual Angle! vision scientists often measure size in visual angle! visual angle object size / object distance in degree! visual angle in!
21 Visual Acuity! Roorda & Williams, 1999, Nature! each photorecepter! ~ 1 arc min (1/60 of a degree) of visual angle! 5 arcmin visual angle!
22 Snellen chart! Visual Acuity! characters are 5 arc min of visual angle, need to resolve 1 arc min to read!
23 Retina VR Display What does it Take?! need per eye:! 150 x 135 with pixels covering 1 arc min of visual angle = 9000 x 8100 pixels (probably 2-3x of that in practice) biggest challenge: bandwidth!! capture or render stereo panoramas or images at that resolution! compress and transmit huge amount of data! drive and operate display pixels!
24 wikipedia! Relative Acuity Over Retina! Eccentricity (i.e., distance to fovea in degrees of visual angle)!
25 Density of Photoreceptors on Retina! 100K! Rods! superior! Patney et al. 2016! Density (per mm2)! 10K! 1K! 100! Cones! Ganglion Cells! nasal! inferior! temporal! 10! 0! 20! 40! 60! 80! Eccentricity (degrees)!
26 Density of Photoreceptors on Retina! 100K! Rods! superior! Patney et al. 2016! Density (per mm2)! 10K! 1K! 100! Cones! Ganglion Cells! nasal! inferior! temporal! superior, but! other directions! are similar! 10! 0! 20! 40! 60! 80! Eccentricity (degrees)!
27 Density of Photoreceptors on Retina! fovea: 1-5! 100K! Rods! superior! Patney et al. 2016! Density (per mm2)! 10K! 1K! 100! Cones! Ganglion Cells! nasal! inferior! temporal! 10! 0! 20! 40! 60! 80! Eccentricity (degrees)!
28 Acuity Over Retina / MAR! acuity falls off due to:! reduced receptor and ganglion cell density! reduced optical nerve bandwidth! reduced processing devoted to periphery in the visual cortex!
29 Acuity Over Retina / MAR! acuity falls off due to:! reduced receptor and ganglion cell density! reduced optical nerve bandwidth! reduced processing devoted to periphery in the visual cortex! Guenter et al. 2012! MAR: minimum angle of resolution in deg/cycle! slope! ω = me + ω 0 eccentricity in degrees! smallest resolvable angle at fovea in deg/cycle!
30 Acuity Over Retina / MAR! acuity falls off due to:! reduced receptor and ganglion cell density! reduced optical nerve bandwidth! reduced processing devoted to periphery in the visual cortex! Guenter et al. 2012! MAR: minimum angle of resolution in deg/cycle! slope! ω = me + ω 0 eccentricity in degrees! ω 0 = ( 1/ 48) m = smallest resolvable angle at fovea in deg/cycle! somewhere between 20/20 (30 cycles per degree) and 20/10 (60 cycles per degree)! range of acceptable equivalent for observed image quality!
31 ! Acuity Over Retina / MAR! MAR! Acuity (=1/MAR)! Guenter et al. 2012! MAR (degrees/cycle)! acuity (cycles/degree)! eccentricity (degrees)! eccentricity (degrees)! MAR! slope! ω = me + ω 0 eccentricity in degrees! smallest resolvable angle at fovea in deg/cycle!
32 Patney et al. 2016!
33 Patney et al. 2016!
34 Foveated Rendering! Guenter et al. 2012: split image into n layers, e.g. inner (foveal, 1), middle (2), outer (3)! render image in each zone with progressively lower resolution! goals: save computation & bandwidth!!
35 Foveated Rendering! Guenter et al. 2012: split image into n layers, e.g. inner (foveal, 1), middle (2), outer (3)! MAR! ω 3 MAR! e i = i n fov 2 e 1 = fov 6 e 2 = fov 3 ω 2 ω 1 layer 1! layer 2! layer 3! e 1! e 2! eccentricity (degrees)!
36 Foveated Rendering! MAR! ω 1 is best the display can do!! ω 1 unit of :! degrees cycle = degrees 2 pixel _ size MAR! ω 3 ω 2 ω 1 layer 1! layer 2! layer 3! e 1! e 2! eccentricity (degrees)!
37 Foveated Rendering! MAR! ω 1 is best the display can do!! ω 1 unit of :! degrees cycle = degrees 2 pixel _ size MAR! screen _ size ω 1 = 2 tan 1 screen _ resolution viewer_distance 360 2π ω 3 ω 2 ω 1 layer 1! layer 2! layer 3! e 1! e 2! eccentricity (degrees)! viewer_distance
38 Foveated Rendering! MAR! ω 1 is best the display can do!! ω 1 unit of :! degrees cycle = degrees 2 pixel _ size MAR! screen _ size ω 1 = 2 tan 1 screen _ resolution viewer_distance 360 2π ω 3 ω 2 ω 1 layer 1! layer 2! layer 3! e 1! e 2! eccentricity (degrees)! screen _ size screen _ resolution is either screen width or height (same units as viewer_distance)! is either number of horizontal pixels or vertical pixels of the screen (same dimension as screen_size)!
39 Foveated Rendering! MAR! MAR! screen _ size ω 1 = 2 tan 1 screen _ resolution viewer_distance 360 2π ω 3 ω 2 = me 2 + ω 0 ω 3 = me 3 + ω 0 ω 2 ω 1 layer 1! layer 2! layer 3! e 1! e 2! eccentricity (degrees)!
40 Foveated Rendering! convert MAR (in degrees/cycle) to pixels! MAR! MAR! ω 3 blur _ radius _in _ px = viewer_distance tan ω 2 2π 360 ω 2 ω 1 layer 1! layer 2! layer 3! e 1! e 2! eccentricity (degrees)!
41 Foveated Rendering Performance Gain! m = m = n is number of layers! speedup is total number of display pixels / number of pixels in all layers combined! conclusion: for large fov & high-res displays, we need to shade much fewer pixels!!
42 Depth Perception!
43
44
45
46
47
48
49 Depth Perception! wikipedia!
50 Depth Perception! wikipedia! monocular cues! perspective! relative object size! absolute size! occlusion! accommodation! retinal blur! motion parallax! texture gradients! shading!! binocular cues! (con)vergence! disparity / parallax!!
51 Depth Perception! binocular disparity! convergence! motion parallax! accommodation/blur! current glasses-based (stereoscopic) displays! near-term: light field displays! longer-term: holographic displays!
52 Cutting & Vishton, 1995! Depth Perception!
53 Stereoscopic Displays! Charles Wheatstone., Stereoscope.! Walker, Lewis E., Hon. Abraham Lincoln, President of the United States. Library of Congress!
54 Stereoscopic Displays!
55 Stereoscopic Displays! 176 years later! Charles Wheatstone 1838! stereoscopic displays!
56 A Brief History of Virtual Reality! Stereoscopes! Wheatstone, Brewster,! VR, AR,! Ivan Sutherland! VR explosion! Oculus, Sony, Valve, MS,! 1838! 1968! ! Next-generation VR & AR Displays!
57 Focus Cues!
58 far focus! Oculumotor Processes! 16 years: ~8cm to! 50 years: ~50cm to (mostly irrelevant)! near focus! adithyakiran.wordpress.com!
59 Accommodation and Retinal Blur!
60 Accommodation and Retinal Blur!
61 Accommodation and Retinal Blur!
62 Accommodation and Retinal Blur!
63 Accommodation and Retinal Blur!
64 Accommodation and Retinal Blur!
65 Accommodation and Retinal Blur!
66 Focus Cues Degrade With Age - Presbyopia! Nearest focus distance! 0D ( cm)! 4D (25cm)! 8D (12.5cm)! 12D (8cm)! 16D (6cm)! Bifocals! 8! 16! 24! 32! 40! 48! 56! 64! 72! Age (years)! Duane, 1912!
67 Retinal Blur! pupil controls amount of light! accommodation distance!
68 Retinal Blur! pupil controls amount of light! accommodation distance!
69 Retinal Blur! out of focus blur! accommodation distance! circle of confusion!
70 Retinal Blur! out of focus blur! accommodation distance! circle of confusion!
71 Retinal Blur / Depth of Field Rendering! S c = M D S S 1 f S M = S 1 f f = 17mm accommodation distance: S 1! D! circle of confusion: c!
72 Circle of Confusion! c = M D S S 1 S circle of confusion in m! accommodation distance! distance to eye in m!
73 Held et al., 2006, ACM SIGGRAPH! Blur Affects Relative Object Size!!
74 Real World:!! Vergence & Accommodation Match! Top View!
75 Top View! Screen! Stereo Displays Today:!! Vergence-Accommodation Mismatch!!
76 Vergence-Accommodation Conflict! Marty Banks, UC Berkeley! effects! visual discomfort! visual fatigue! nausea! diplopic vision! eyestrain! compromised image quality! pathologies in developing visual system!!
77 Shibata et al, 2011, Journal of Vision! Zone of Comfort!
78 Summary! visual acuity: 20/20 is ~1 arc min! visual acuity varies over retina: can exploit via foveated rendering! field of view: ~190 monocular, ~120 binocular, ~135 vertical! temporal resolution: ~60 Hz (depends on contrast, luminance)! depth cues in 3D displays: disparity, vergence, accommodation, blur,! accommodation range: ~8cm to, degrades with age!
79 !! References and Further Reading! interesting textbooks on perception:! Wandell, Foundations of Vision, Sinauer Associates,1995! Howard, Perceiving in Depth, Oxford University Press, 2012! foveated rendering:! Guenter, Finch, Drucker, Tan, Snyder Foveated 3D Graphics, ACM SIGGRAPH Asia 2012! Patney, Salvi, Kim, Kaplanyan, Wyman, Benty, Luebke, Lefohn Towards Foveated Rendering for Gaze-Tracked Virtual Reality, ACM SIGGRAPH Asia 2016! depth cues and more:! Cutting & Vishton, Perceiving layout and knowing distances: The interaction, relative potency, and contextual use of different information about depth, Epstein and Rogers (Eds.), Perception of space and motion, 1995! Held, Cooper, O Brien, Banks, Using Blur to Affect Perceived Distance and Size, ACM Transactions on Graphics, 2010! Hoffman and Banks, Focus information is used to interpret binocular images. Journal of Vision 10, 2010! Hoffman, Girshick, Akeley, and Banks, Vergence-accommodation conflicts hinder visual performance and cause visual fatigue. Journal of Vision 8, 2008! Huang, Chen, Wetzstein, The Light Field Stereoscope, ACM SIGGRAPH 2015! the retina, visual acuity, visual field! Roorda, Williams, The arrangement of the three cone classes in the living human eye, Nature, Vol 397, 1999! Snellen chart: Ruch and Fulton, Medical physiology and biophysics, 1960! contrast sensitivity function & hybrid images:! Oliva, Torralba, Schyns, Hybrid Images, ACM Transactions on Graphics (SIGGRAPH), 2006! Spatio-temporal CSF: Kelly, Motion and Vision. II. Stabilized spatio-temporal threshold surface, Journal of the Optical Society of America,1979!!
Virtual Reality ll. Visual Imaging in the Electronic Age. Donald P. Greenberg November 16, 2017 Lecture #22
Virtual Reality ll Visual Imaging in the Electronic Age Donald P. Greenberg November 16, 2017 Lecture #22 Fundamentals of Human Perception Retina, Rods & Cones, Physiology Receptive Fields Field of View
Multidimensional image retargeting
Multidimensional image retargeting 9:00: Introduction 9:10: Dynamic range retargeting Tone mapping Apparent contrast and brightness enhancement 10:45: Break 11:00: Color retargeting 11:30: LDR to HDR 12:20:
Realtime 3D Computer Graphics Virtual Reality
Realtime 3D Computer Graphics Virtual Reality Human Visual Perception The human visual system 2 eyes Optic nerve: 1.5 million fibers per eye (each fiber is the axon from a neuron) 125 million rods (achromatic
Basic distinctions. Definitions. Epstein (1965) familiar size experiment. Distance, depth, and 3D shape cues. Distance, depth, and 3D shape cues
Distance, depth, and 3D shape cues Pictorial depth cues: familiar size, relative size, brightness, occlusion, shading and shadows, aerial/ atmospheric perspective, linear perspective, height within image,
Visual Acuity. Adler s Physiology of the Eye 11th Ed. Chapter 33 - by Dennis Levi.
Visual Acuity Adler s Physiology of the Eye 11th Ed. Chapter 33 - by Dennis Levi http://www.mcgill.ca/mvr/resident/ Visual Acuity Keeness of Sight, possible to be defined in different ways Minimum Visual
PERCEIVING DEPTH AND SIZE
PERCEIVING DEPTH AND SIZE DEPTH Cue Approach Identifies information on the retina Correlates it with the depth of the scene Different cues Previous knowledge Slide 3 Depth Cues Oculomotor Monocular Binocular
Visual Rendering for VR. Stereo Graphics
Visual Rendering for VR Hsueh-Chien Chen, Derek Juba, and Amitabh Varshney Stereo Graphics Our left and right eyes see two views, which are processed by our visual cortex to create a sense of depth Computer
Stereo Graphics. Visual Rendering for VR. Passive stereoscopic projection. Active stereoscopic projection. Vergence-Accommodation Conflict
Stereo Graphics Visual Rendering for VR Hsueh-Chien Chen, Derek Juba, and Amitabh Varshney Our left and right eyes see two views, which are processed by our visual cortex to create a sense of depth Computer
Stereovision. Binocular disparity
Stereovision Binocular disparity Retinal correspondence Uncrossed disparity Horoptor Crossed disparity Horoptor, crossed and uncrossed disparity Wheatsteone stereoscope (c. 1838) Red-green anaglyph How
Visual Acuity. Visual acuity
Visual Acuity Excerpts from a lecture by: Harold E. Bedell Physiological Optics & Vision Science Visual acuity Visual acuity is the smallest spatial detail that can be detected or identified. Types of
Visual Acuity. Excerpts from a lecture by: Harold E. Bedell. Physiological Optics & Vision Science
Visual Acuity Excerpts from a lecture by: Harold E. Bedell Physiological Optics & Vision Science Visual acuity Visual acuity is the smallest spatial detail that can be detected or identified. Types of
Binocular cues to depth PSY 310 Greg Francis. Lecture 21. Depth perception
Binocular cues to depth PSY 310 Greg Francis Lecture 21 How to find the hidden word. Depth perception You can see depth in static images with just one eye (monocular) Pictorial cues However, motion and
ENGINEERING Electrical Engineering
ENGINEERING Electrical Engineering Virtual Reality EE 267, Spring 2017 Assignment 3 due 4/27/2017 at 11:59 PM Topics: Foveated Rendering, Depth of Field, Stereo Rendering, Anaglyph 3D Students should use
Assessing vergence-accommodation conflict as a source of discomfort in stereo displays
Assessing vergence-accommodation conflict as a source of discomfort in stereo displays Joohwan Kim, Takashi Shibata, David Hoffman, Martin Banks University of California, Berkeley * This work is published
Foveated 3D Graphics. Brian Guenter Mark Finch Steven Drucker Desney Tan John Snyder. Microsoft Research
Foveated 3D Graphics Brian Guenter Mark Finch Steven Drucker Desney Tan John Snyder Microsoft Research High resolution image Foveal vision: 2-5 Acuity falloff with eccentricity e e Using Foveation Human
Prof. Feng Liu. Spring /27/2014
Prof. Feng Liu Spring 2014 http://www.cs.pdx.edu/~fliu/courses/cs510/ 05/27/2014 Last Time Video Stabilization 2 Today Stereoscopic 3D Human depth perception 3D displays 3 Stereoscopic media Digital Visual
Vision: From Eye to Brain (Chap 3)
Vision: From Eye to Brain (Chap 3) Lecture 7 Jonathan Pillow Sensation & Perception (PSY 345 / NEU 325) Princeton University, Fall 2017 early visual pathway eye eye optic nerve optic chiasm optic tract
Conflict? What conflict?
Conflict? What conflict? Peter Howarth, PhD Environmental Ergonomics Research Centre What s the problem? According to a study of 400 filmgoers by L Mark Carrier, of California State University, 3D
POVS Basic Vision Science Core. Visual Acuity
POVS Basic Vision Science Core Visual Acuity Visual acuity Visual acuity is the smallest spatial detail that can be detected or identified. Types of acuity tasks: Detection acuity Resolution acuity Localization
USE R/G GLASSES. Binocular Combina0on of Images. What can happen when images are combined by the two eyes?
Binocular Combina0on of Images 3D D USE R/G GLASSES What can happen when images are combined by the two eyes? Fusion- when images are similar and disparity is small Monocular Suppression / Rivalry- when
Google Daydream
Current VR Devices Current VR Devices Most of these new devices include slight improvements, primarily involved with tracking (both location and orientation) and obtaining better accuracy Google Daydream
Perception, Part 2 Gleitman et al. (2011), Chapter 5
Perception, Part 2 Gleitman et al. (2011), Chapter 5 Mike D Zmura Department of Cognitive Sciences, UCI Psych 9A / Psy Beh 11A February 27, 2014 T. M. D'Zmura 1 Visual Reconstruction of a Three-Dimensional
Important concepts in binocular depth vision: Corresponding and non-corresponding points. Depth Perception 1. Depth Perception Part II
Depth Perception Part II Depth Perception 1 Binocular Cues to Depth Depth Information Oculomotor Visual Accomodation Convergence Binocular Monocular Static Cues Motion Parallax Perspective Size Interposition
Computational Perception. Visual Coding 3
Computational Perception 15-485/785 February 21, 2008 Visual Coding 3 A gap in the theory? - - + - - from Hubel, 1995 2 Eye anatomy from Hubel, 1995 Photoreceptors: rods (night vision) and cones (day vision)
Adaptive Image Sampling Based on the Human Visual System
Adaptive Image Sampling Based on the Human Visual System Frédérique Robert *, Eric Dinet, Bernard Laget * CPE Lyon - Laboratoire LISA, Villeurbanne Cedex, France Institut d Ingénierie de la Vision, Saint-Etienne
Image Formation. CS418 Computer Graphics Eric Shaffer.
Image Formation CS418 Computer Graphics Eric Shaffer http://graphics.cs.illinois.edu/cs418/fa14 Some stuff about the class Grades probably on usual scale: 97 to 93: A 93 to 90: A- 90 to 87: B+ 87 to 83:
CS 563 Advanced Topics in Computer Graphics Stereoscopy. by Sam Song
CS 563 Advanced Topics in Computer Graphics Stereoscopy by Sam Song Stereoscopy Introduction Parallax Camera Displaying and Viewing Results Stereoscopy What is it? seeing in three dimensions creates the
Visualizing Flow Fields by Perceptual Motion
Visualizing Flow Fields by Perceptual Motion Li-Yi Wei Wei-Chao Chen Abstract Visualizing flow fields has a wide variety of applications in scientific simulation and computer graphics. Existing approaches
lecture 10 - depth from blur, binocular stereo
This lecture carries forward some of the topics from early in the course, namely defocus blur and binocular disparity. The main emphasis here will be on the information these cues carry about depth, rather
Modeling the top neuron layers of the human retina. Laurens Koppenol ( ) Universiteit Utrecht
Modeling the top neuron layers of the human retina Laurens Koppenol (3245578) 23-06-2013 Universiteit Utrecht 1 Contents Introduction... 3 Background... 4 Photoreceptors... 4 Scotopic vision... 5 Photopic
3D Display and AR. Linda Li, Rokid Rlab Dec. 27, 2016
3D Display and AR Linda Li, Rokid Rlab Dec. 27, 2016 1 Five OLED Trends of Future Tactile / Haptic Touch Displays Higher Pixel Density Glasses-free 3D Virtue Reality and Augmented Reality 1 Stereoscopic
Outline. Immersive Visual Communication Pipeline. Lec 02 Human Vision System
Outline CS/EE 5590 / (Class Ids: 44873, 44874) Fall 2016, Tue 5-8:15pm@Edu Room 260 Special Topics: Advanced Multimedia Communication Lec 02 Human Vision System Re-Cap of Lec 01 Human Vision System Human
The Graphics Pipeline and OpenGL IV: Stereo Rendering, Depth of Field Rendering, Multi-pass Rendering!
! The Graphics Pipeline and OpenGL IV: Stereo Rendering, Depth of Field Rendering, Multi-pass Rendering! Gordon Wetzstein! Stanford University! EE 267 Virtual Reality! Lecture 6! stanford.edu/class/ee267/!!
Stereoscopic Systems Part 1
Stereoscopic Systems Part 1 Terminology: Stereoscopic vs. 3D 3D Animation refers to computer animation created with programs (like Maya) that manipulate objects in a 3D space, though the rendered image
Natural Viewing 3D Display
We will introduce a new category of Collaboration Projects, which will highlight DoCoMo s joint research activities with universities and other companies. DoCoMo carries out R&D to build up mobile communication,
Stereoscopic & Collimated Display Requirements
01 Stereoscopic & Collimated Display Requirements October 3, 01 Charles J. Lloyd President, Visual Performance LLC Overview Introduction Stereoscopic displays Antialiasing and pixel pitch Collimated displays
Computer and Machine Vision
Computer and Machine Vision Lecture Week 4 Part-2 February 5, 2014 Sam Siewert Outline of Week 4 Practical Methods for Dealing with Camera Streams, Frame by Frame and De-coding/Re-encoding for Analysis
BINOCULAR DISPARITY AND DEPTH CUE OF LUMINANCE CONTRAST. NAN-CHING TAI National Taipei University of Technology, Taipei, Taiwan
N. Gu, S. Watanabe, H. Erhan, M. Hank Haeusler, W. Huang, R. Sosa (eds.), Rethinking Comprehensive Design: Speculative Counterculture, Proceedings of the 19th International Conference on Computer- Aided
Neurophysical Model by Barten and Its Development
Chapter 14 Neurophysical Model by Barten and Its Development According to the Barten model, the perceived foveal image is corrupted by internal noise caused by statistical fluctuations, both in the number
Miniature faking. In close-up photo, the depth of field is limited.
Miniature faking In close-up photo, the depth of field is limited. http://en.wikipedia.org/wiki/file:jodhpur_tilt_shift.jpg Miniature faking Miniature faking http://en.wikipedia.org/wiki/file:oregon_state_beavers_tilt-shift_miniature_greg_keene.jpg
Introduction to Neural Networks Overview of the visual system
Introduction to Neural Networks Overview of the visual system November 2, 2011 Daniel Kersten Goals Provide an overview of a major brain subsystem to help anchor concepts in neural network theory. Discuss
Think-Pair-Share. What visual or physiological cues help us to perceive 3D shape and depth?
Think-Pair-Share What visual or physiological cues help us to perceive 3D shape and depth? [Figure from Prados & Faugeras 2006] Shading Focus/defocus Images from same point of view, different camera parameters
EBU TECHNOLOGY AND DEVELOPMENT. The EBU and 3D. Dr Hans Hoffmann. Dr David Wood. Deputy Director. Programme Manager
EBU TECHNOLOGY AND DEVELOPMENT The EBU and 3D - What are we doing - Dr David Wood Deputy Director Dr Hans Hoffmann Programme Manager Is it the beer or the 3D that s giving me a headache? It is very easy
Comparison of Accommodation and Convergence by Simultaneous Measurements during 2D and 3D Vision Gaze
Comparison of Accommodation and Convergence by Simultaneous Measurements during 2D and 3D Vision Gaze Hiroki Hori 1, Tomoki Shiomi 1, Tetsuya Kanda 1, Akira Hasegawa 1, Hiromu Ishio 1, Yasuyuki Matsuura
Visual Pathways to the Brain
Visual Pathways to the Brain 1 Left half of visual field which is imaged on the right half of each retina is transmitted to right half of brain. Vice versa for right half of visual field. From each eye
All human beings desire to know. [...] sight, more than any other senses, gives us knowledge of things and clarifies many differences among them.
![All human beings desire to know. [...] sight, more than any other senses, gives us knowledge of things and clarifies many differences among them.](/thumbs/91/106597332.jpg "All human beings desire to know. [...] sight, more than any other senses, gives us knowledge of things and clarifies many differences among them.")
All human beings desire to know. [...] sight, more than any other senses, gives us knowledge of things and clarifies many differences among them. - Aristotle University of Texas at Arlington Introduction
Binocular Stereo Vision
Binocular Stereo Vision Properties of human stereo vision Marr-Poggio-Grimson multi-resolution stereo algorithm CS332 Visual Processing Department of Computer Science Wellesley College Properties of human
Human Perception of Objects
Human Perception of Objects Early Visual Processing of Spatial Form Defined by Luminance, Color, Texture, Motion, and Binocular Disparity David Regan York University, Toronto University of Toronto Sinauer
Multi-projector-type immersive light field display
Multi-projector-type immersive light field display Qing Zhong ( é) 1, Beishi Chen (í ì) 1, Haifeng Li (Ó ô) 1, Xu Liu ( Ê) 1, Jun Xia ( ) 2, Baoping Wang ( ) 2, and Haisong Xu (Å Ø) 1 1 State Key Laboratory
Introduction to visual computation and the primate visual system
Introduction to visual computation and the primate visual system Problems in vision Basic facts about the visual system Mathematical models for early vision Marr s computational philosophy and proposal
Project 4 Results. Representation. Data. Learning. Zachary, Hung-I, Paul, Emanuel. SIFT and HoG are popular and successful.
Project 4 Results Representation SIFT and HoG are popular and successful. Data Hugely varying results from hard mining. Learning Non-linear classifier usually better. Zachary, Hung-I, Paul, Emanuel Project
TOWARDS A DESCRIPTIVE DEPTH INDEX FOR 3D CONTENT: MEASURING PERSPECTIVE DEPTH CUES
TOWARDS A DESCRIPTIVE DEPTH INDEX FOR 3D CONTENT: MEASURING PERSPECTIVE DEPTH CUES Lutz Goldmann, Touradj Ebrahimi Ecole Polyt. Federale de Lausanne Multimedia Signal Processing Group Lausanne, Switzerland
Video Communication Ecosystems. Research Challenges for Immersive. over Future Internet. Converged Networks & Services (CONES) Research Group
Research Challenges for Immersive Video Communication Ecosystems over Future Internet Tasos Dagiuklas, Ph.D., SMIEEE Assistant Professor Converged Networks & Services (CONES) Research Group Hellenic Open
CS5670: Computer Vision
CS5670: Computer Vision Noah Snavely Light & Perception Announcements Quiz on Tuesday Project 3 code due Monday, April 17, by 11:59pm artifact due Wednesday, April 19, by 11:59pm Can we determine shape
HAMED SARBOLANDI SIMULTANEOUS 2D AND 3D VIDEO RENDERING Master s thesis
HAMED SARBOLANDI SIMULTANEOUS 2D AND 3D VIDEO RENDERING Master s thesis Examiners: Professor Moncef Gabbouj M.Sc. Payman Aflaki Professor Lauri Sydanheimo Examiners and topic approved by the Faculty Council
Convergence Point Adjustment Methods for Minimizing Visual Discomfort Due to a Stereoscopic Camera
J. lnf. Commun. Converg. Eng. 1(4): 46-51, Dec. 014 Regular paper Convergence Point Adjustment Methods for Minimizing Visual Discomfort Due to a Stereoscopic Camera Jong-Soo Ha 1, Dae-Woong Kim, and Dong
CSE 4392/5369. Dr. Gian Luca Mariottini, Ph.D.
University of Texas at Arlington CSE 4392/5369 Introduction to Vision Sensing Dr. Gian Luca Mariottini, Ph.D. Department of Computer Science and Engineering University of Texas at Arlington WEB : http://ranger.uta.edu/~gianluca
DEPTH PERCEPTION. Learning Objectives: 7/31/2018. Intro & Overview of DEPTH PERCEPTION** Speaker: Michael Patrick Coleman, COT, ABOC, & former CPOT
DEPTH PERCEPTION Speaker: Michael Patrick Coleman, COT, ABOC, & former CPOT Learning Objectives: Attendees will be able to 1. Explain what the primary cue to depth perception is (vs. monocular cues) 2.
Mahdi Amiri. May Sharif University of Technology
Course Presentation Multimedia Systems 3D Technologies Mahdi Amiri May 2014 Sharif University of Technology Binocular Vision (Two Eyes) Advantages A spare eye in case one is damaged. A wider field of view
IEEE Consumer Electronics Society Calibrating a VR Camera. Adam Rowell CTO, Lucid VR
IEEE Consumer Electronics Society Calibrating a VR Camera Adam Rowell CTO, Lucid VR adam@lucidcam.com Virtual Reality Cameras Lucid VR Camera How Does it Work? Lucid Software Technology Recording: Synchronization
zspace Developer SDK Guide - Introduction Version 1.0 Rev 1.0
zspace Developer SDK Guide - Introduction Version 1.0 zspace.com Developer s Guide Rev 1.0 zspace, Inc. 2015. zspace is a registered trademark of zspace, Inc. All other trademarks are the property of their
Stereo. Shadows: Occlusions: 3D (Depth) from 2D. Depth Cues. Viewing Stereo Stereograms Autostereograms Depth from Stereo
Stereo Viewing Stereo Stereograms Autostereograms Depth from Stereo 3D (Depth) from 2D 3D information is lost by projection. How do we recover 3D information? Image 3D Model Depth Cues Shadows: Occlusions:
Augmented Reality: Easy on the Eyes 26 OPTICS & PHOTONICS NEWS FEBRUARY 2015
Augmented Reality: 26 OPTICS & PHOTONICS NEWS FEBRUARY 2015 Easy on the Eyes Hong Hua and Bahram Javidi Artist s interpretation of augmented-reality view, applied to the Pyramide du Louvre, Paris, France.
CSc I6716 Spring D Computer Vision. Introduction. Instructor: Zhigang Zhu City College of New York
Introduction CSc I6716 Spring 2012 Introduction Instructor: Zhigang Zhu City College of New York zzhu@ccny.cuny.edu Course Information Basic Information: Course participation p Books, notes, etc. Web page
Crosstalk reduces the amount of depth seen in 3D images of natural scenes
Crosstalk reduces the amount of depth seen in 3D images of natural scenes Inna Tsirlin *, Robert S. Allison and Laurie M. Wilcox Centre for Vision Research, York University, 4700 Keele st., Toronto, ON,
Head Mounted Display Optics I!
! Head Mounted Display Optics I! Gordon Wetzstein! Stanford University! EE 267 Virtual Reality! Lecture 7! stanford.edu/class/ee267/!! ! Logistics! HW3 is probably the longest homework, so get started
MEASUREMENT OF PERCEIVED SPATIAL RESOLUTION IN 3D LIGHT-FIELD DISPLAYS
MEASUREMENT OF PERCEIVED SPATIAL RESOLUTION IN 3D LIGHT-FIELD DISPLAYS Péter Tamás Kovács 1, 2, Kristóf Lackner 1, 2, Attila Barsi 1, Ákos Balázs 1, Atanas Boev 2, Robert Bregović 2, Atanas Gotchev 2 1
3D Computer Vision. Introduction. Introduction. CSc I6716 Fall Instructor: Zhigang Zhu City College of New York
Introduction CSc I6716 Fall 2010 3D Computer Vision Introduction Instructor: Zhigang Zhu City College of New York zzhu@ccny.cuny.edu Course Information Basic Information: Course participation Books, notes,
VS 117 LABORATORY III: FIXATION DISPARITY INTRODUCTION
VS 117 LABORATORY III: FIXATION DISPARITY INTRODUCTION Under binocular viewing, subjects generally do not gaze directly at the visual target. Fixation disparity is defined as the difference between the
ABSTRACT Purpose. Methods. Results.
ABSTRACT Purpose. Is there a difference in stereoacuity between distance and near? Previous studies produced conflicting results. We compared distance and near stereoacuities using identical presentation
Visual Perception. Basics
Visual Perception Basics Please refer to Colin Ware s s Book Some materials are from Profs. Colin Ware, University of New Hampshire Klaus Mueller, SUNY Stony Brook Jürgen Döllner, University of Potsdam
Lenses: Focus and Defocus
Lenses: Focus and Defocus circle of confusion A lens focuses light onto the film There is a specific distance at which objects are in focus other points project to a circle of confusion in the image Changing
Robert Collins CSE486, Penn State Lecture 08: Introduction to Stereo
Lecture 08: Introduction to Stereo Reading: T&V Section 7.1 Stereo Vision Inferring depth from images taken at the same time by two or more cameras. Basic Perspective Projection Scene Point Perspective
Depth cue integration: stereopsis and image blur
Vision Research 40 (2000) 3501 3506 www.elsevier.com/locate/visres Depth cue integration: stereopsis and image blur George Mather *, David R.R. Smith Laboratory of Experimental Psychology, Biology School,
Stereo-Foveation for Anaglyph Imaging
Stereo-Foveation for Anaglyph Imaging Arzu Coltekin (Çöltekin) Helsinki University of Technology, Institute of Photogrammetry and Remote Sensing, FIN-02015 Espoo, Finland arzu.coltekin @ hut.fi ABSTRACT
Colorado School of Mines. Computer Vision. Professor William Hoff Dept of Electrical Engineering &Computer Science.
Professor William Hoff Dept of Electrical Engineering &Computer Science http://inside.mines.edu/~whoff/ 1 Stereo Vision 2 Inferring 3D from 2D Model based pose estimation single (calibrated) camera > Can
Real-time Generation and Presentation of View-dependent Binocular Stereo Images Using a Sequence of Omnidirectional Images
Real-time Generation and Presentation of View-dependent Binocular Stereo Images Using a Sequence of Omnidirectional Images Abstract This paper presents a new method to generate and present arbitrarily
CS4670: Computer Vision
CS4670: Computer Vision Noah Snavely Lecture 30: Light, color, and reflectance Light by Ted Adelson Readings Szeliski, 2.2, 2.3.2 Light by Ted Adelson Readings Szeliski, 2.2, 2.3.2 Properties of light
Multi-View Geometry (Ch7 New book. Ch 10/11 old book)
Multi-View Geometry (Ch7 New book. Ch 10/11 old book) Guido Gerig CS-GY 6643, Spring 2016 gerig@nyu.edu Credits: M. Shah, UCF CAP5415, lecture 23 http://www.cs.ucf.edu/courses/cap6411/cap5415/, Trevor
Vergence Micromovements and Depth Perception
Vergence Micromovements and Depth Perception Antonio Francisco * CVAP, Royal Institute of Technology (KTH) S-100 44 Stockholm, Sweden Abstract A new approach in stereo vision is proposed in which 3D depth
Interactive Stable Ray Tracing
Interactive Stable Ray Tracing Alessandro Dal Corso 1,2, Marco Salvi 1, Craig Kolb 1, Jeppe Revall Frisvad 2, Aaron Lefohn 1, David Luebke 1 1 NVIDIA, 2 Technical University of Denmark Comparison with
Thanks to Chris Bregler. COS 429: Computer Vision
Thanks to Chris Bregler COS 429: Computer Vision COS 429: Computer Vision Instructor: Szymon Rusinkiewicz TA: Linjie Luo smr@cs.princeton.edu linjiel@cs.princeton.edu Course web page http://www.cs.princeton.edu/courses/archive/fall09/cos429/
THERE ARE two primary unwanted effects in 3-D TV:
482 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 23, NO. 3, MARCH 2013 Visual Comfort Enhancement for Stereoscopic Video Based on Binocular Fusion Characteristics Donghyun Kim,
Stereoscopic media. 3D is hot today. 3D has a long history. 3D has a long history. Digital Visual Effects Yung-Yu Chuang
3D is hot today Stereoscopic media Digital Visual Effects Yung-Yu Chuang 3D has a long history 1830s, stereoscope 1920s, first 3D film, The Power of Love projected dual-strip in the red/green anaglyph
Stereo: Disparity and Matching
CS 4495 Computer Vision Aaron Bobick School of Interactive Computing Administrivia PS2 is out. But I was late. So we pushed the due date to Wed Sept 24 th, 11:55pm. There is still *no* grace period. To
Interaxial Distance and Convergence Control for Efficient Stereoscopic Shooting using Horizontal Moving 3D Camera Rig
Interaxial Distance and Convergence Control for Efficient Stereoscopic Shooting using Horizontal Moving 3D Camera Rig Seong-Mo An, Rohit Ramesh, Young-Sook Lee and Wan-Young Chung Abstract The proper assessment
Bio-inspired Binocular Disparity with Position-Shift Receptive Field
Bio-inspired Binocular Disparity with Position-Shift Receptive Field Fernanda da C. e C. Faria, Jorge Batista and Helder Araújo Institute of Systems and Robotics, Department of Electrical Engineering and
Computer Vision. I-Chen Lin, Assistant Professor Dept. of CS, National Chiao Tung University
Computer Vision I-Chen Lin, Assistant Professor Dept. of CS, National Chiao Tung University About the course Course title: Computer Vision Lectures: EC016, 10:10~12:00(Tues.); 15:30~16:20(Thurs.) Pre-requisites:
Perceptually-Motivated Graphics, Visualization and 3D Displays
Perceptually-Motivated Graphics, Visualization and 3D Displays Ann McNamara Department of Visualization Texas A&M University Katerina Mania Department of Electronic & Computer Engineering Technical University
Improving visual function diagnostic metrics. Charles Campbell
Improving visual function diagnostic metrics Charles Campbell Metrics - What are they? What are they used for? A metric assigns a numerical value or a set of values to characterize some chosen phenomenon
Active Fixation Control to Predict Saccade Sequences Supplementary Material
Active Fixation Control to Predict Saccade Sequences Supplementary Material Calden Wloka Iuliia Kotseruba John K. Tsotsos Department of Electrical Engineering and Computer Science York University, Toronto,
Lecture 14: Computer Vision
CS/b: Artificial Intelligence II Prof. Olga Veksler Lecture : Computer Vision D shape from Images Stereo Reconstruction Many Slides are from Steve Seitz (UW), S. Narasimhan Outline Cues for D shape perception
Light. Properties of light. What is light? Today What is light? How do we measure it? How does light propagate? How does light interact with matter?
Light Properties of light Today What is light? How do we measure it? How does light propagate? How does light interact with matter? by Ted Adelson Readings Andrew Glassner, Principles of Digital Image
IDE-3D: Predicting Indoor Depth Utilizing Geometric and Monocular Cues
2016 International Conference on Computational Science and Computational Intelligence IDE-3D: Predicting Indoor Depth Utilizing Geometric and Monocular Cues Taylor Ripke Department of Computer Science
PSYCHOMETRIC ASSESSMENT OF STEREOSCOPIC HEAD-MOUNTED DISPLAYS
PSYCHOMETRIC ASSESSMENT OF STEREOSCOPIC HEAD-MOUNTED DISPLAYS Logan Williams 1, Charles Lloyd 2, James Gaska 1, Charles Bullock 1, and Marc Winterbottom 1 1 OBVA Laboratory, USAF School of Aerospace Medicine,
What have we leaned so far?
What have we leaned so far? Camera structure Eye structure Project 1: High Dynamic Range Imaging What have we learned so far? Image Filtering Image Warping Camera Projection Model Project 2: Panoramic
Real-Time Graphics Architecture
RealTime Graphics Architecture Kurt Akeley Pat Hanrahan http://www.graphics.stanford.edu/courses/cs448a01fall About Kurt Personal history B.E.E. Univeristy of Delaware, 1980 M.S.E.E. Stanford, 1982 SGI
Processing Framework Proposed by Marr. Image
Processing Framework Proposed by Marr Recognition 3D structure; motion characteristics; surface properties Shape From stereo Motion flow Shape From motion Color estimation Shape From contour Shape From
Evaluation of Geometric Depth Estimation Model for Virtual Environment
Evaluation of Geometric Depth Estimation Model for Virtual Environment Puneet Sharma 1, Jan H. Nilsen 1, Torbjørn Skramstad 2, Faouzi A. Cheikh 3 1 Department of Informatics & E-Learning (AITeL), Sør Trøndelag
Stereo Optical Company Vision Tester Slide Package:
Stereo Optical Company Vision Tester Slide Package: F.A.C.T. Contrast Sensitivity Test for Distance and Near, Acuity,Color, Phorias, Stereopsis, and Potential Acuity. Ideal for Clinical or Research Practices.