===!"§ Deutsche Telekom Laboratories Target Acquisition with Camera Phones when used as Magic...

===!"§Deutsche Telekom Laboratories

Target Acquisition with Camera Phoneswhen used as Magic LensesCHI 2008, Florence, Italy, April 9, 2008

Michael Rohs

Deutsche Telekom LaboratoriesTechnische Universität Berlin

Antti Oulasvirta

Helsinki Institute for Information Technology HIIT

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Deutsche Telekom Laboratories

See-Through Interfaces for Camera Phones

Augmented reality (AR) applications project information onto real world scenery in real time

—Camera phone shows this layer through narrow viewport

Navigation by moving the device—Spatially-aware displays [Fitzmaurice]—Peephole displays [Yee]

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Magic Lens for Paper Maps

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Magic Lens for AR Widgets

Printable user interface elements

—Embedded in user’s environment

—Entry point for interaction—Controlled via position, rotation,

distance Background layer

—Passive widget Overlay layer

—Active Display—Camera phone as “see-through

tool”

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Dynamic Peephole Pointing & Magic Lens Pointing

Dynamic peephole pointing

Movement of peephole corresponds to movement through virtual space

No visual context beyond display

Targets dynamically revealed

Magic lens pointing Camera phone tracks its

position above a meaningful background

Visual context beyond display

Targets always visible

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Target Acquisition with Camera Phones

Two distinct categories of interfaces—Dynamic peephole: Objects of interest only in virtual—Magic lens: Objects of interest on the physical surface

Analyzing target acquisition with camera phones—Performance—Modeling

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Overview

Analysis of the Pointing Tasks Two-Component Model of Magic Lens Pointing Experiment 1: Dynamic Peephole Pointing Experiment 2: Magic Lens Pointing

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Target Acquisition with Camera Phones

View selection Screen distance range System delay Maximum movement velocity Display update rate Device movement in 3D space Gaze deployment between display and

background

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Analysis of Dynamic Peephole Pointing Task

Task: Move cursor onto target

Target might not be visible in the peephole initially Visual feedback uniformly mediated by the device

Hypothesis: Dynamic peephole pointing can be modeled by Fitts’ law

MT = ao + bo ID with ID = log2(D / W + 1)

Lag and low frame rates increase the coefficients ao and bo compared to direct observation of the target

W

D

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Analysis of Magic Lens Pointing Task


First phase: Target directly visibleFirst task: Move lens over target

Second phase: Target behind displaySecond task: Move crosshair over target

T

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Analysis of Magic Lens Pointing Task


First phase: Target directly visibleMTp = ap + bp log2(D / S + 1)

Second phase: Target behind displayMTv = av + bv log2(S/2 / W + 1)

S W

W

S/2

D

T

S

D

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Magic Lens Pointing Model

First phase (physical pointing): MTp = ap + bp log2(D / S + 1)

Second phase (virtual pointing): MTv = av + bv log2(S/2 / W + 1)

Two-component Fitts’ law modelMT = MTp + MTv

= a + b log2(D / S + 1) + c log2(S/2 / W + 1)

S W

D

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physical pointing

Control Loops in Physical Pointing

Iterative corrections model [Crossman & Goodeve]

—Derive Fitts’ law from number of iterations through feedback loop

—Movements >200 ms controlled by visual feedback—Ballistic submovements of constant time (135-290 ms)—Each submovement has distance error (4-7%)

observe target distance P = 100 ms

plan hand movement C = 70 ms

perform hand movement M = 70 ms

expected distance error

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Control Loops in Virtual Pointing

Virtual pointing introduces delay in feedback loop

Machine lag and frame rate [Ware & Balakrishnan]

Time for submovement t = P + C + M and machine lag L

Rewrite two-part model asMT = a + β t log2(D / S + 1) + γ (t + L) log2(S/2 / W + 1) observe target distance

P = 100 ms

plan hand movement

perform hand movement

expected distance error

C = 70 ms

M = 70 ms

virtual pointingcompute device position

L = 100–300 ms

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Dynamic Peephole Pointing Experiment

Targets only visible on device display Device tracked on surface of size A0 Cyclical multi-direction target acquisition

(ISO 9241-9) 9 targets on a circle, next one highlighted Nokia N80 for tracking and feedback (beeps, highlighting) 12 participants (10 male, 2 female, age 22-33) Task: Move crosshair over target and press joystick

button Instructed to calibrate z-distance and explore space

before start W = 13-97 mm, D = 55-535 mm, 33 combinations

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Results of Dynamic Peephole Pointing

12 subjects x 33 conditions x 3 rounds x 9 selections

Mean movement time: 2.13 sec Mean error rate: 5%

0%

5%

10%

15%

20%

0 1 2 3 4 5 6 7 8 9 10

W [cm]

erro

r ra

te

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Fitts’ Law Model of Dynamic Peephole Pointing

Basic Fitts’ law leads to accurate predictions MT = a + b log2(D / W + 1)

= -636 + 881 log2(D / W + 1), R2 = 0.93

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5ID

MT

[se

c]

MT = a + b log2 (D / W + 1)

a = 0.636, b = 0.881R2 = 0.93

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.50

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

ID

MT

[se

c]

-

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Magic Lens Pointing Experiment

Targets visible on background and through lens Device tracked on plasma display of size A0 Cyclical multi-direction target acquisition

(ISO 9241-9) 9 targets on a circle, next one highlighted Nokia 6630 for tracking and feedback (beeps,

highlighting) 12 participants (8 male, 4 female, age 19-31) Task: Move crosshair over target and press joystick

button Instructed to calibrate z-distance before start W = 13-97 mm, D = 55-535 mm, 33 combinations

===!"§


Results of Magic Lens Pointing

12 subjects x 33 conditions x 3 rounds x 9 selections

Mean movement time: 1.22 sec Mean error rate: 7%

0%

5%

10%

15%

20%

0 1 2 3 4 5 6 7 8 9 10

W [cm]

erro

r ra

te

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Fitts’ Law Model of Magic Lens Pointing

Fitts’ law does not accurately predict performance

MT = 581 + 191 log2(D / W + 1), R2 = 0.57

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.50

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

ID

MT

[sec

]

MT = a + b log2 ( D / W + 1)a = 0.581, b = 0. 191R2 = 0.57

MT

[sec

]

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Two-Part Fitts’ Law Model of Magic Lens Pointing

Two-component Fitts’ law leads to better prediction

Screen diagonal S = 2.8 cm MT = a + b log2(D / S + 1) + c log2(S/2 / W +

1)= 383 + 112 log2(D / S + 1) + 811

log2(S/2 / W + 1), R2 = 0.88

1 1.2 1.4 1.6 1.8 2

1

1.2

1.4

1.6

1.8

2

predicted MT [sec]

mea

sure

dM

T [s

ec]

MT = a + b log2 (D / S + 1) + c log2(S/2 / W)

S = 2.8 cma = 0.383, b = 0.112, c = 0.811

R2 = 0.88

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Two-Part Fitts’ Law Model with Parameters a, b, c, S

Treating lens size S as an additional parameter MT = 384 + 113 log2(D / 2.99 + 1)

+ 776 log2(2.99/2 / W + 1), R2 = 0.88

Screen diagonal predicted to 2.99 cm (real value 2.8 cm)

Supports the validity of the model

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Conclusion

Analyzed target acquisition with camera phones as—Dynamic peephole displays—Magic lenses

Dynamic peephole pointing can be modeled with Fitts’ law—Interaction uniformly mediated by the device

Magic lens pointing not adequately explainable by Fitts’ law

—Initial physical pointing phase—Second virtual pointing phase

Developed two-part Fitts’ law model for magic lens pointing

—MT = a + b log2(D / S + 1) + c log2(S/2 / W + 1)

Numerous application ideas for magic lens interfaces

===!"§ Deutsche Telekom Laboratories Target Acquisition with Camera Phones when used as Magic...

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