2016 AR Summer School Lecture2

103
LECTURE 2: AUGMENTED REALITY TECHNOLOGY Mark Billinghurst AR Summer School February 15 th – 19 th 2016 University of South Australia

Transcript of 2016 AR Summer School Lecture2

Page 1: 2016 AR Summer School Lecture2

LECTURE 2: AUGMENTED REALITY TECHNOLOGY

Mark Billinghurst

AR Summer School February 15th – 19th 2016 University of South Australia

Page 2: 2016 AR Summer School Lecture2

Augmented Reality Definition • Defining Characteristics [Azuma 97]

• Combines Real and Virtual Images • Both can be seen at the same time

• Interactive in real-time • The virtual content can be interacted with

• Registered in 3D • Virtual objects appear fixed in space

Azuma, R. T. (1997). A survey of augmented reality. Presence, 6(4), 355-385.

Page 3: 2016 AR Summer School Lecture2

Augmented Reality Technology

! Combining Real and Virtual Images •  Display technologies

! Interactive in Real-Time •  Input and interactive technologies

! Registered in 3D •  Viewpoint tracking technologies

Display

Processing

Input Tracking

Page 4: 2016 AR Summer School Lecture2

AR Displays

Page 5: 2016 AR Summer School Lecture2

AR Displays

e.g. window reflections

Virtual Images seen off windows

e.g. Reach-In

Projection CRT Display using beamsplitter

Not Head-Mounted

e.g. Shared Space Magic Book

Liquid Crystal Displays LCDs

Head-Mounted Display (HMD)

Primarily Indoor Environments

e.g. WLVA and IVRD

Cathode Ray Tube (CRT) or Virtual Retinal Display (VRD)

Many Military Applications & Assistive Technologies

Head-Mounted Display (HMD)

e.g. Head-Up Display (HUD)

Projection Display Navigational Aids in Cars

Military Airborne Applications

Not Head Mounted (e.g. vehicle mounted)

Primarily Outdoor (Daylight) Environments

AR Visual Displays

Page 6: 2016 AR Summer School Lecture2

Display Technologies ! Types (Bimber/Raskar 2003)

! Head attached •  Head mounted display/projector

! Body attached •  Handheld display/projector

! Spatial •  Spatially aligned projector/monitor

Page 7: 2016 AR Summer School Lecture2

Display Taxonomy

Page 8: 2016 AR Summer School Lecture2

Head Mounted Displays

Page 9: 2016 AR Summer School Lecture2

Head Mounted Displays (HMD) • Display and Optics mounted on Head • May or may not fully occlude real world •  Provide full-color images • Considerations

•  Cumbersome to wear •  Brightness •  Low power consumption •  Resolution limited •  Cost is high?

Page 10: 2016 AR Summer School Lecture2

Key Properties of HMD • Field of View

• Human eye 95 degrees horizontal, 60/70 degrees vertical

• Resolution •  > 320x240 pixel

• Refresh Rate • Focus

•  Fixed/manual

• Power • Size

Page 11: 2016 AR Summer School Lecture2

Types of Head Mounted Displays

Occluded See-thru

Multiplexed

Page 12: 2016 AR Summer School Lecture2

Immersive VR Architecture

Head!Tracker

Host !Processor

Data Base!Model

Rendering!Engine Frame!

Buffer

head position/orientation

to network Display!Driver

Non see-thru!

Image source &

optics

virtual object

Virtual World

Page 13: 2016 AR Summer School Lecture2

See-thru AR Architecture

Head!Tracker

Host !Processor

Data Base!Model

Rendering!Engine Frame!

Buffer

head position/orientation

to network Display!Driver

see-thru!combiner

Virtual Image superimposed!over real world object

real world

Image source

Page 14: 2016 AR Summer School Lecture2

Optical see-through head-mounted display

Virtual images from monitors

Real World

Optical Combiners

Page 15: 2016 AR Summer School Lecture2

Optical See-Through HMD

Page 16: 2016 AR Summer School Lecture2

Epson Moverio BT-200

▪ Stereo see-through display ($700) ▪  960 x 540 pixels, 23 degree FOV, 60Hz, 88g ▪ Android Powered, separate controller ▪ VGA camera, GPS, gyro, accelerometer

Page 17: 2016 AR Summer School Lecture2

View Through Optical See-Through HMD

Page 18: 2016 AR Summer School Lecture2

The Virtual Retinal Display

•  Image scanned onto retina • Commercialized through Microvision

•  Nomad System - www.mvis.com

Page 19: 2016 AR Summer School Lecture2

Strengths of optical see-through AR

• Simpler (cheaper) • Direct view of real world

• Full resolution, no time delay (for real world) • Safety • Lower distortion

• No eye displacement • but COASTAR video see-through avoids this

Page 20: 2016 AR Summer School Lecture2

Video AR Architecture

Head!Tracker

Host !Processor

Graphics!renderer

Digital!Mixer Frame!

Buffer

head position/orientation

to network Display!Driver

Non see-thru!

Image source &

optics

Head-mounted camera

aligned to display optics

Video!Processor

Video image of real world

Virtual image inset into video of real world

Page 21: 2016 AR Summer School Lecture2

Video see-through HMD

Video cameras

Monitors

Graphics

Combiner

Video

Page 22: 2016 AR Summer School Lecture2

Video See-Through HMD

Page 23: 2016 AR Summer School Lecture2

Vuzix Wrap 1200DXAR

▪ Stereo video see-through display ($1500) ■ Twin 852 x 480 LCD displays, 35 deg. FOV ■ Stereo VGA cameras ■ 3 DOF head tracking

Page 24: 2016 AR Summer School Lecture2

View Through a Video See-Through HMD

Page 25: 2016 AR Summer School Lecture2

Strengths of Video See-Through AR • True occlusion

• Kiyokawa optical display that supports occlusion

• Digitized image of real world • Flexibility in composition • Matchable time delays • More registration, calibration strategies

• Wide FOV is easier to support

Page 26: 2016 AR Summer School Lecture2

Optical vs. Video AR Summary

• Both have proponents • Video is more popular today?

• Likely because lack of available optical products

• Depends on application? • Manufacturing: optical is cheaper • Medical: video for calibration strategies

Page 27: 2016 AR Summer School Lecture2

Eye multiplexed AR Architecture

Head!Tracker

Host !Processor

Data Base!Model

Rendering!Engine Frame!

Buffer

head position/orientation

to network Display!Driver

Virtual Image inset into!real world scene

real world

Opaque!Image source

Page 28: 2016 AR Summer School Lecture2

Virtual Image ‘inset’ into real

Page 29: 2016 AR Summer School Lecture2

Google Glass

Page 30: 2016 AR Summer School Lecture2

View Through Google Glass

Page 31: 2016 AR Summer School Lecture2
Page 32: 2016 AR Summer School Lecture2

Vuzix M-100

▪ Monocular multiplexed display ($1000) ■ 852 x 480 LCD display, 15 deg. FOV ■ 5 MP camera, HD video ■ GPS, gyro, accelerometer

Page 33: 2016 AR Summer School Lecture2

Display Technology

•  Curved Mirror •  off-axis projection •  curved mirrors in front of eye •  high distortion, small eye-box

•  Waveguide •  use internal reflection •  unobstructed view of world •  large eye-box

Page 34: 2016 AR Summer School Lecture2

See-through thin displays

•  Waveguide techniques for thin see-through displays •  Wider FOV, enable AR applications •  Social acceptability

Opinvent Ora

Lumus DK40

Page 35: 2016 AR Summer School Lecture2

Spatial/Projected AR

Page 36: 2016 AR Summer School Lecture2

Spatial Augmented Reality

• Project onto irregular surfaces • Geometric Registration •  Projector blending, High dynamic range

• Book: Bimber, Rasker “Spatial Augmented Reality”

Page 37: 2016 AR Summer School Lecture2

Projector-based AR

Examples: Raskar, MIT Media Lab Inami, Tachi Lab, U. Tokyo

Projector

Real objects with retroreflective covering

User (possibly head-tracked)

Page 38: 2016 AR Summer School Lecture2

Example of projector-based AR

Ramesh Raskar, UNC, MERL

Page 39: 2016 AR Summer School Lecture2

Example of projector-based AR

Ramesh Raskar, UNC Chapel Hill

Page 40: 2016 AR Summer School Lecture2

Head Mounted Projector

• NVIS P-50 HMPD •  1280x1024/eye •  Stereoscopic •  50 degree FOV •  www.nvis.com

Page 41: 2016 AR Summer School Lecture2

HMD vs. HMPD

Head Mounted Display Head Mounted Projected Display

Page 42: 2016 AR Summer School Lecture2

CastAR - http://technicalillusions.com/

• Stereo head worn projectors •  Interactive wand • Rollable retro-reflective sheet

Page 43: 2016 AR Summer School Lecture2

• Designed for shared interaction

Page 44: 2016 AR Summer School Lecture2

Pico Projectors

• Microvision - www.mvis.com • 3M, Samsung, Philips, etc

Page 45: 2016 AR Summer School Lecture2

MIT Sixth Sense

• Body worn camera and projector • http://www.pranavmistry.com/projects/sixthsense/

Page 46: 2016 AR Summer School Lecture2

Other AR Displays

Page 47: 2016 AR Summer School Lecture2

Video Monitor AR

Video cameras Monitor

Graphics Combiner

Video

Stereo glasses

Page 48: 2016 AR Summer School Lecture2

Examples

Page 49: 2016 AR Summer School Lecture2

Virtual Showcase

• Mirrors on a projection table • Head tracked stereo • Up to 4 users • Merges graphic and real objects •  Exhibit/museum applications

• Fraunhofer Institute (2001) •  Bimber, Frohlich

Page 50: 2016 AR Summer School Lecture2

Augmented Paleontology

Bimber et. al. IEEE Computer Sept. 2002

Page 51: 2016 AR Summer School Lecture2

Alternate Displays

LCD Panel Laptop PDA

Page 52: 2016 AR Summer School Lecture2

Handheld Displays

• Mobile Phones • Camera • Display • Input

Page 53: 2016 AR Summer School Lecture2

Other Types of AR Display • Audio

•  spatial sound •  ambient audio

•  Tactile •  physical sensation

• Haptic •  virtual touch

Page 54: 2016 AR Summer School Lecture2

Haptic Input

• AR Haptic Workbench •  CSIRO 2003 – Adcock et. al.

Page 55: 2016 AR Summer School Lecture2

Phantom

• Sensable Technologies (www.sensable.com) • 6 DOF Force Feedback Device

Page 56: 2016 AR Summer School Lecture2

AR Haptic Interface

•  Phantom, ARToolKit, Magellan

Page 57: 2016 AR Summer School Lecture2

AR Tracking and Registration

Page 58: 2016 AR Summer School Lecture2

Objects Registered in 3D

• Registration • Positioning virtual object wrt real world

• Tracking • Continually locating the users viewpoint

•  Position (x,y,z), Orientation (r,p,y)

Page 59: 2016 AR Summer School Lecture2

Tracking Requirements

• Augmented Reality Information Display • World Stabilized •  Body Stabilized • Head Stabilized

Increasing Tracking Requirements

Head Stabilized Body Stabilized World Stabilized

Page 60: 2016 AR Summer School Lecture2

Tracking Technologies "  Active

•  Mechanical, Magnetic, Ultrasonic •  GPS, Wifi, cell location

"  Passive •  Inertial sensors (compass, accelerometer, gyro) •  Computer Vision

•  Marker based, Natural feature tracking

"  Hybrid Tracking •  Combined sensors (eg Vision + Inertial)

Page 61: 2016 AR Summer School Lecture2

Tracking Types

Magnetic Tracker

Inertial Tracker

Ultrasonic Tracker

Optical Tracker

Marker-Based Tracking

Markerless Tracking

Specialized Tracking

Edge-Based Tracking

Template-Based Tracking

Interest Point Tracking

Mechanical Tracker

Page 62: 2016 AR Summer School Lecture2

Mechanical Tracker

• Idea: mechanical arms with joint sensors

• ++: high accuracy, haptic feedback • -- : cumbersome, expensive

Microscribe

Page 63: 2016 AR Summer School Lecture2

Magnetic Tracker • Idea: difference between a magnetic transmitter and a receiver

• ++: 6DOF, robust • -- : wired, sensible to metal, noisy, expensive

Flock of Birds (Ascension)

Page 64: 2016 AR Summer School Lecture2

Magnetic Tracking Error

Page 65: 2016 AR Summer School Lecture2

Global Positioning System (GPS)

• Created by US in 1978 • Currently 29 satellites

• Satellites send position + time • GPS Receiver positioning

•  4 satellites need to be visible • Differential time of arrival •  Triangulation

• Accuracy •  5-30m+, blocked by weather, buildings etc

Page 66: 2016 AR Summer School Lecture2

Inertial Tracker •  Idea: measuring linear and angular orientation rates (accelerometer/gyroscope)

• ++: no transmitter, cheap, small, high frequency, wireless •  -- : drift, hysteris only 3DOF

IS300 (Intersense) Wii Remote

Page 67: 2016 AR Summer School Lecture2

Mobile Sensors •  Inertial compass

•  Earth’s magnetic field •  Measures absolute orientation

• Accelerometers •  Measures acceleration about axis •  Used for tilt, relative rotation •  Can drift over time

Page 68: 2016 AR Summer School Lecture2

Optical Tracking

Page 69: 2016 AR Summer School Lecture2

Optical Tracking Technologies

• Scalable active trackers •  InterSense IS-900, 3rd Tech HiBall

• Passive optical computer vision • Line of sight, may require landmarks • Can be brittle. • Computer vision is computationally-intensive

3rd Tech, Inc.

Page 70: 2016 AR Summer School Lecture2

Outside-In vs. Inside-Out Tracking

Page 71: 2016 AR Summer School Lecture2

HiBall Tracking System (3rd Tech) •  Inside-Out Tracker

•  $50K USD

•  Scalable over large area •  Fast update (2000Hz) •  Latency Less than 1 ms.

• Accurate •  Position 0.4mm RMS •  Orientation 0.02° RMS

Page 72: 2016 AR Summer School Lecture2
Page 73: 2016 AR Summer School Lecture2

Marker tracking

•  Available for more than 10 years •  Several open source solutions exist

•  ARToolKit, ARTag, ATK+, etc

•  Fairly simple to implement •  Standard computer vision methods

•  A rectangle provides 4 corner points •  Enough for pose estimation!

Page 74: 2016 AR Summer School Lecture2

Marker Based Tracking: ARToolKit

http://artoolkit.sourceforge.net/

Page 75: 2016 AR Summer School Lecture2

Coordinate Systems

Page 76: 2016 AR Summer School Lecture2

Tracking challenges in ARToolKit

False positives and inter-marker confusion (image by M. Fiala)

Image noise (e.g. poor lens, block

coding / compression, neon tube)

Unfocused camera, motion blur

Dark/unevenly lit scene, vignetting

Jittering (Photoshop illustration)

Occlusion (image by M. Fiala)

Page 77: 2016 AR Summer School Lecture2
Page 78: 2016 AR Summer School Lecture2

Markerless Tracking

Magnetic Tracker Inertial Tracker

Ultrasonic Tracker

Optical Tracker

Marker-Based Tracking

Markerless Tracking

Specialized Tracking

Edge-Based Tracking

Template-Based Tracking

Interest Point Tracking

• No more Markers! #Markerless Tracking

Mechanical Tracker

Page 79: 2016 AR Summer School Lecture2

Natural Feature Tracking

• Use Natural Cues of Real Elements •  Edges •  Surface Texture •  Interest Points

• Model or Model-Free • No visual pollution

Contours

Features Points

Surfaces

Page 80: 2016 AR Summer School Lecture2

Texture Tracking

Page 81: 2016 AR Summer School Lecture2

Edge Based Tracking • RAPiD [Drummond et al. 02]

•  Initialization, Control Points, Pose Prediction (Global Method)

Page 82: 2016 AR Summer School Lecture2

Line Based Tracking • Visual Servoing [Comport et al. 2004]

Page 83: 2016 AR Summer School Lecture2

Model Based Tracking

• OpenTL - www.opentl.org • General purpose library for model based visual tracking

Page 84: 2016 AR Summer School Lecture2

Marker vs. natural feature tracking •  Marker tracking

•  ++ Markers can be an eye-catcher •  ++ Tracking is less demanding •  -- The environment must be instrumented with markers •  -- Markers usually work only when fully in view

•  Natural feature tracking •  -- A database of keypoints must be stored/downloaded •  ++ Natural feature targets might catch the attention less •  ++ Natural feature targets are potentially everywhere •  ++ Natural feature targets work also if partially in view

Page 85: 2016 AR Summer School Lecture2

Example: Outdoor Hybrid Tracking

• Combines •  computer vision

•  natural feature tracking

•  inertial gyroscope sensors • Both correct for each other

•  Inertial gyro - provides frame to frame prediction of camera orientation

• Computer vision - correct for gyro drift

Page 86: 2016 AR Summer School Lecture2

Outdoor AR Tracking System

You, Neumann, Azuma outdoor AR system (1999)

Page 87: 2016 AR Summer School Lecture2

Robust Outdoor Tracking

• Hybrid Tracking • Computer Vision, GPS, inertial

• Going Out •  Reitmayr & Drummond (Univ. Cambridge)

Reitmayr, G., & Drummond, T. W. (2006). Going out: robust model-based tracking for outdoor augmented reaity. In Mixed and Augmented Reality, 2006. ISMAR 2006. IEEE/ACM International Symposium on (pp. 109-118). IEEE.

Page 88: 2016 AR Summer School Lecture2

Handheld Display

Page 89: 2016 AR Summer School Lecture2

Registration

Page 90: 2016 AR Summer School Lecture2

Spatial Registration

Page 91: 2016 AR Summer School Lecture2

The Registration Problem

•  Virtual and Real must stay properly aligned •  If not:

•  Breaks the illusion that the two coexist •  Prevents acceptance of many serious applications

Page 92: 2016 AR Summer School Lecture2

Sources of registration errors

• Static errors • Optical distortions • Mechanical misalignments • Tracker errors • Incorrect viewing parameters

• Dynamic errors • System delays (largest source of error)

• 1 ms delay = 1/3 mm registration error

Page 93: 2016 AR Summer School Lecture2

Reducing static errors

• Distortion compensation • Manual adjustments • View-based or direct measurements • Camera calibration (video)

Page 94: 2016 AR Summer School Lecture2

View Based Calibration (Azuma 94)

Page 95: 2016 AR Summer School Lecture2

Dynamic errors

•  Total Delay = 50 + 2 + 33 + 17 = 102 ms •  1 ms delay = 1/3 mm = 33mm error

Tracking Calculate Viewpoint Simulation

Render Scene

Draw to Display

x,y,z r,p,y

Application Loop

20 Hz = 50ms 500 Hz = 2ms 30 Hz = 33ms 60 Hz = 17ms

Page 96: 2016 AR Summer School Lecture2

Reducing dynamic errors (1)

• Reduce system lag • Faster components/system modules

• Reduce apparent lag • Image deflection • Image warping

Page 97: 2016 AR Summer School Lecture2

Reducing System Lag

Tracking Calculate Viewpoint Simulation

Render Scene

Draw to Display

x,y,z r,p,y

Application Loop

Faster Tracker Faster CPU Faster GPU Faster Display

Page 98: 2016 AR Summer School Lecture2

Reducing Apparent Lag

Tracking Update

x,y,z r,p,y

Virtual Display

Physical Display

(640x480)

1280 x 960

Last known position

Virtual Display

Physical Display

(640x480)

1280 x 960

Latest position

Tracking Calculate Viewpoint Simulation

Render Scene

Draw to Display

x,y,z r,p,y

Application Loop

Page 99: 2016 AR Summer School Lecture2

Reducing dynamic errors (2) • Match input streams (video)

•  Delay video of real world to match system lag

•  Predictive Tracking •  Inertial sensors helpful

Azuma / Bishop 1994

Page 100: 2016 AR Summer School Lecture2

Predictive Tracking

Time

Position

Past Future

Can predict up to 80 ms in future (Holloway)

Now

Page 101: 2016 AR Summer School Lecture2

Predictive Tracking (Azuma 94)

Page 102: 2016 AR Summer School Lecture2

Wrap-up • Tracking and Registration are key problems • Registration error

• Measures against static error • Measures against dynamic error

• AR typically requires multiple tracking technologies • Research Areas:

• Hybrid Markerless Techniques, Deformable Surface, Mobile, Outdoors

Page 103: 2016 AR Summer School Lecture2

www.empathiccomputing.org

@marknb00

[email protected]