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Interaction Error based Viewpoint Estimation for Continuous Parallax Error Correction on Interactive Screens Bastian Migge (ETH Zurich), Andreas Kunz (ETH Zurich), Tim Schmidt (PARC)

Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

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Page 1: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Interaction Error based Viewpoint Estimation for Continuous Parallax

Error Correction on Interactive Screens

Bastian Migge (ETH Zurich), Andreas Kunz (ETH Zurich), Tim Schmidt (PARC)

Page 2: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Content

n  Introduction/Motivation: Interactive surfaces n  Problem: Parallax error n  Calibration Techniques n  Model based viewpoint estimation n  Contribution: Empirical observation model for MPC

–  User study –  Discrete Observation Model

n  Conclusion and outlook

Bastian Migge © 06/2011 IWF, ETH Zurich 2

Page 3: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Interactive Surfaces

n  Pros –  Intuitive operation, easy to learn –  Innate interaction (input and output combined)

n  Requisition –  Good alignment between image plane and

tracking system is essential

3

Digital Desk (Crion table, ETH Zurich)

Single display groupware (Collaboard, ETH Zurich)

Ticketing machine (New York Underground)

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 4: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Parallax Error

4

n  Vz : Distance between image and interaction plane

n  Vx : Resulting parallax distortion in x-dimension

n  ax,z: Distance from user to interaction point in x,z

z

xzx a

aVV ⋅=Parallax Error

Interaction plane and image pane with offset1 (analogous for y)

1 Source: Migge,Kunz: User Model for Predictive Calibration Control on Interactive Screens, IEEE CW 2010

Image plane

Interaction plane4

Vx

User A

23

1

ax

az

Vz

z

xy

User B

5

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 5: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Static Calibration

n  Initially to correct geometric distortion n  A-priori setup n  Is biased by user characteristics

(height, arm length) n  Depends on a single viewpoint

n  Can not deal with user’s motion n  Can not handle multiple users n  Can not overcome the parallax error

stemming from changing viewpoints (VP)

5

Static Calibration Process

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 6: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Continuous Calibration with Viewpoint Estimation

n  Method1: –  Remove sensors - Estimate users viewpoint –  Add filter – model the users position and movement –  Set the correction for the next (predicted position) interaction –  Consider effect of correction actions (user disturbance)

à  Model based Predictive Parallax Error Correction under Uncertainty (POMDP)

n  Pro –  No additional hardware

n  Cons –  Models needed (a priori) –  Interaction on screen needed (at runtime)

6 Bastian Migge © 06/2011 IWF, ETH Zurich

1[Migge, Kunz, Schmidt: POMDP Models for Continuous Calibration of Interactive Surfaces, AAAI SS 2010]

Page 7: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Model based Predictive Parallax Error Correction under Uncertainty

n  Parallax correction (-Vx): shift pointing device information n  Information sources

–  Target can be assumed to be next to Touch point –  Viewpoint is not directly observable –  VP can be inferred from GUI interactions (ß Vx, Vz)

n  Benefits –  Correction for all touch points –  Increases the pointing accuracy

7

Image plane

Interaction plane

Vx

User's viewpoint

Touch point

Target

xz

Vz

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 8: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Contribution: Viewpoint estimation from interaction error

8

n  Contribution: A model of the user’s interaction behavior to estimate the viewpoint of the user

n  Static Characteristics: –  Display offset Iz

n  Dynamic Values: –  Relative User position VPx –  Relative Interaction Error Ix –  VPx ~ Ix

n  Observation Model: –  Pr(Ix = err |VPx = vp)

Image plane

Interaction plane

User

Target

VPzz

xy

InteractionIz

VPx

Ix

Dependency between relative viewpoint and relative pointing error

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 9: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

User Study – Measurement Setup

n  Participants: 13(4) (fe)male, avg. age 31.05, avg. height 179mm n  Interactive System

–  50“ interactive surface (plasma screen with SMART tracking) –  Pixel pitch 0.858 x 0.808 mm, Resolution 1280 x 768 px –  On-screen target: 15 x 15 px (13 x 12 mm) –  Parallax offset ≥ 13 mm

à Measures the Interaction error (in 2D display coordinates)

9

(b) Assembly of the tracking system on top of the display (a) Schematic measurement setup with test person

10

6.4

652.6

[mm]

Touch sensitive film

Glas plane

Displaybody

Pen

785

mm

1215

mm

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 10: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

User Study - Task

n  Random clicker –  User must click a single button of a full screen application –  Button moves after each interaction –  Python, QT, X11, Linux system

à Provides global interaction position on display

10 Bastian Migge © 06/2011 IWF, ETH Zurich

Test application

Page 11: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

User Study – Tracking Setup

n  Tracking System: Qualisys Motion Tracking System –  4 Oqus 300 Camera –  IR based out-side in system –  Measures Position of reflective marker (passive) –  50 Hz; σ = 0.87 mm

à Measures the 3D Viewpoint and transforms 2D display coordinates to global 3D coordinate system

11

(b) Passive marker on interactive screen (a) Head tracking module 1http://www.qualisys.com

1

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 12: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Vertical measurements

User Study – Results 1/2 Pointing Error

12

n  Pointing error n  Deviation from

assumed hit point (haptic error)

Boxplots Horizontal measurements

−40 −20 0 20 40 60

0.00

0.05

0.10

0.15

0.20

Error [mm]

Inte

ract

ions

[%]

Pointing ErrorDeviation from assumed hit

−40 −20 0 20 40

0.00

0.05

0.10

0.15

0.20

Error [mm]

Inte

ract

ions

[%]

Pointing ErrorDeviation from assumed hit

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nPointing error Deviation from assumed hit point

Image plane

Interaction plane4

User

z

xytarget

actual hit point

assumed viewpointassumed hit point

Deviation from assumed hit

Bastian Migge © 06/2011 IWF, ETH Zurich

Pointing error and Haptic error

Page 13: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

User Study – Results 2/2 Correlation

13

n  Normalized viewpoint interaction error n  5500 interactions

Horizontal measurements Vertical measurements

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−0.8 −0.6 −0.4 −0.2 0.0 0.2 0.4 0.6

−1.0

−0.5

0.0

0.5

Pearsons correlation coefficient ( 0.806 )

Viewpoint

Inte

ract

ion

erro

r

Least square fitLowess fit

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−0.6 −0.4 −0.2 0.0 0.2 0.4

−1.0

−0.5

0.0

0.5

Pearsons correlation coefficient ( 0.011 )

Viewpoint

Inte

ract

ion

erro

r

Least square fitLowess fit

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 14: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Data interpretation: Discrete Observation Model

n  Measurement Data: Correlation between Interaction error and Viewpoint

n  Allows the controller to infer the viewpoint from the interaction error

n  Set up the Discrete Model –  Observation space O –  State space S –  P(O|S=s) as probability

distribution

14

inferred viewpoint

image plane

interaction plane

applied correction

actual viewpoint

ohit orightoleft

targetcenter

Observation (O) model for a given viewpoint and target (S) as discrete probability distribution P(O|S)

Bastian Migge © 06/2011 IWF, ETH Zurich

Page 15: Interaction Error based Viewpoint Estimation for ... · User Study – Tracking Setup ! Tracking System: Qualisys Motion Tracking System – 4 Oqus 300 Camera – IR based out-side

Discrete Observation Model Concrete Example

n  Continuous observation space, Discrete states –  Click error significantly differs for different viewpoints

n  Discrete observation space

15

Horizontal click error for 5 discrete viewpoint states

● ●

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

[ −1 , −0.55 ) [ −0.15 , 0.15 ) [ 0.55 , 1 )

−1.0

−0.5

0.0

0.5

Viewpoint (State)

Clic

kerro

r (O

bser

vatio

n)

Observation model ( #states= 5 #observations= 5 )Relative click error

[ −0.15 , 0.15 ) mean −0.286 var 0.065

Den

sity

−2 −1 0 1 2

0.0

0.5

1.0

1.5

P(O|s=“left”)

Observation model ( #states= 5 #observations= 5 )Relative click error

[ 0.15 , 0.55 ) mean 0.202 var 0.036

Den

sity

−2 −1 0 1 2

0.0

0.5

1.0

1.5

P(O|s=“right”)

Bastian Migge © 06/2011 IWF, ETH Zurich

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Conclusion and Outlook

n  Focus was to model the correlation between viewpoint position and interaction error on the screen –  Viewpoint can be distinguished

n  model the user’s behavior exists

n  Complete empirical model –  The correlation between pointing accuracy and target size –  Effect of correction actions onto the user

n  Develop prototype –  Prove of concept –  Compare controller to classical correction methods and

tracking based correction

16 Bastian Migge © 06/2011 IWF, ETH Zurich

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Bastian Migge

[email protected]

17 Bastian Migge © 06/2011 IWF, ETH Zurich

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Continuous Calibration with Viewpoint Tracking

n  Methods: –  Visual marker tracking or –  Video image feature extraction

n  Pro –  High quality viewpoint position

n  Cons –  Marker at tracked object not applicable –  Additional camera hardware –  Initial calibration pose needed –  Camera lens opening angle critical

18

3D Skelton Tracking with Microsoft Kinect and OpenNI

1http://luka.tnode.com/gallery/projects-and-work/kinect-hackery/skeleton-tracking

Bastian Migge © 06/2011 IWF, ETH Zurich

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Model based Predictive Parallax Error Correction under Uncertainty – in detail

n  Control: Set the interaction correction parameter Vx, Vy

n  Uncertainty: Interaction error on screen (Observations) does indicate the viewpoint under uncertainty

n  Predictive: Model the User’s behavior predicting his movement 1

n  Method: Partial Observable Markow Decision Process (POMDP) –  User’s behavior modeled as time discrete Markow Chain

(state space) –  Add control à Markow Decision Process (MDP) –  Uncertain measurements indicate states (POMDP)

n  Needs a model of the user’s interaction behavior

19 Bastian Migge © 06/2011 IWF, ETH Zurich

1[Migge, Kunz :User Model for Predictive Calibration Control on Interactive Screens, IEEE CW 2010]