ogic - kristien ooms - eye tracking in the geo-domain: a perception on cartography, navigation and...

EYE TRACKING IN THE GEO-DOMAIN

A PERCEPTION ON CARTOGRAPHY, NAVIGATION AND LANDSCAPE DESIGN

Research Conducted at the Landscape & CartoGIS Research Unit, Department of Geography, Ghent University

Kristien Ooms Fanny Van den HauteLien Dupont Annelies IncoulPieter Laseure Pepijn ViaenePhilippe De Maeyer Nico Van de Weghe Veerle Van Eetvelde

InDOG – 13-16/10/2014Palacký University – Olomouc

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Eye tracking in the Geo-Domain

1. Visual impact of wind turbines in the landscape•Master Thesis Fanny Van den Haute

2. The use of eye tracking in landscape perception research•PhD Research Lien Dupont

3. Search strategies on time intervals in 1D and 2d representations•Master Thesis Pieter Laseure

4. Comparing paper and digital maps using eye tracking•Master Thesis Annelies Incoul

5. Influence of toponyms’ colours on their readability•PhD Research Rasha Deeb

6. Maps, how do users see them?•PhD & PostDoc research Kristien Ooms

7. In search of indoor landmarks •Master Thesis and PhD research Pepijn Viaene


VISUAL IMPACT OF WIND TURBINES IN THE LANDSCAPE

MASTER THESISFANNY VAN DEN HAUTE


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Research Objective & Questions

▪Sustainable energy >> wind turbines >> spatial planning• Appropriate in the landscape?• Visual impact?

▪ Research Questions• How do people look at a landscape with wind turbines?• Is there a difference before and after placement of the wind turbines?• Is there a difference due to personal characteristics (expertise)?• Does the type of landscape play any role in this?


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Research Objective & Questions

▪Stimuli•Panoramic photos•Simulations in photoshop•5 different landscape types•60 pictures in total•7 seconds free viewing

• Participants• 15 experts• 29 non-experts


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Resultaten ▪Wind turbine

• Viewed at after avg 1,5 s • 86,8 % eye catchers• 86,3% longest viewings

▪Wind turbine vs. other vertical objects• Faster• More and longer fixations• Shorter first fixation• More returned movements

1. How do people look at a landscape with wind turbines?

2. Is there a difference before and after placement of the wind turbines?

3. Is there a difference due to personal characteristics (expertise)?

4. Does the type of landscape play any role in this?

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ResultatenEye catchers

• Type changes > wind turbine• Viewed at faster

Fixations• More and longer fixations• More returned movements• Cause: presence wind turbines

WIND TURBINES HAVEA VISUAL IMPACT





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ResultatenSimilarity• Type eye catcher> wind turbine• Type longest viewed object > wind turbine• Timing of viewings• Number of fixations

Difference• Experts shorter fixations

EXPERTISE HAS NO INFLUENCEON VIEWING PATTERN






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Resultaten Similarity

• Timing of perceiving wind turbine

Difference• Type eye catcher and object viewed at longest

- industrial and infrastructural landscapes wind turbines less dominant

• Timings of eye catcher- Woody area > hill or open rural area

TYPE OF LANDSCAPE HAS INFLUENCEON VIEWING PATTERN






THE USE OF EYE-TRACKING IN LANDSCAPE PERCEPTION

RESEARCH

PHD RESEARCHLIEN DUPONT


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Research Questions

Which elements in a landscape catch the attention and in which context are they most eye-catching?

Important for the location of new infrastructures

ObserverRepresentation

Landscape

Observations of landscapes are influenced by…


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Research QuestionsHow do people observe landscapes in general?

•Influence of the photograph properties?‒Focal length, horizontal and vertical view angles

•Influence of the landscape characteristics?‒Degree of openness‒Degree of heterogeneity

•Influence of the social/professional background of the observer?‒Landscape experts versus novices

•Influence of type of landscape? ‒Degree of urbanisation‒Landscape experts versus novices‒Predict viewing pattern?

Exp

erim

ent

1E

xper

imen

t 2

Exp

erim

ent

3


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Study design – Experiment 1 Photograph sampling

90 photographs in total

18 landscapes

Focal length

Horizontal view angle

Vertical view angle

a) Panoramic photograph

50mm 70° 20,9°

b) Standard photograph

50mm 31° 20,9°

c) Zoom 1 70mm 22,4° 15°

d) Zoom 2 100mm 15,8° 10,5°

e) Wide angle photograph

18mm 75,1° 54,3°

23 participants (geographers)


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Ope

n S

emi-o

pen

Enc

lose

d

Homogeneous Heterogeneous

21 landscape expert participants

90 photographs in total

23 novice participants


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Study design – Experiment 2&3


21 landscape expert participants

74 photographs, differing in degree of urbanisation

21 novice participants

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Methodology

Eye tracking technology• Non-portable RED-system (SMI)

Eye tracking experiments• Random order • 5 or 10 seconds per photograph • Free-viewing

• Measured eye tracking metrics• Fixations: number, duration (ms)• Saccades: number, amplitude (°), velocity (°/s)• Derived products: focus maps


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Results – Experiment 1


More information extraction

Shorter fixation duration

Easier information extraction

More saccades Larger saccades Faster saccades

Stronger visual exploration

More fixations Shorter saccades

Panoramic Open Less & longer fixations Less saccades

Weaker visual exploration

Homogeneous Less fixations Less & longer saccades

Weaker visual exploration

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Expert Novice More

fixations & saccades

Less fixations & saccades

Shorter fixations

Longer fixations

Longer scan path

Shorter scan path

Larger visual span

Smaller visual span

Smaller Voronoi

cells

Larger Vorornoi

cells

Scan paths

Focus maps

Voronoi cells

Results – Experiment 2

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1050 x 1680 matrices

Correlation between focus maps and saliency maps?

Saliency map

Focus map


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Results experiment 3

▪Significant effect of landscape type, ▪No effect of expertstatus, no significant interaction▪Non-experts’ viewing pattern is a little more predictable


SEARCH STRATEGIES ON TIME INTERVALS IN 1D AND 2D

REPRESENTATIONS

MASTER THESISPIETER LASEURE


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Research Objective

Evaluate added value of theTriangular Model

to depict time intervals, compared to the ‘traditional’Linear Model


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Relevance and Research Questions▪Importance in education:

“How to depict temporal information most efficiently?”

▪Research Questions:

•Is the TM a clearer / more efficient model than the LM?

•Do males and females search differently in these models?

•Do students and experts search differently in these models?

•Can we distinguish differences in the users search strategies; TM vs. LM?


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Study Design

LM TM 25 novice participant; some removed 3 expert participants

8 stimuli & questions for LM 8 stimuli & questions for TM

Similar questions Mixed Alternate

Quantitative analyses Response time Score Fixation duration Saccadic length

Qualitative analyses


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Results: QuantitativeStudents’ response time

Students’ nr of fixations per second

GROUP nrAVG. SCORE

LM

AVG. SCORE

TMPREFERENCE

Students 25 5,48/10 8,3/10 TM (25/25)

Experts 3 4,75/10 8/10 TM (3/3)

Participants’ preference and score attributed to the modelsStudents’ fixation duration

Students’ saccadic length

Students’ score

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Results: Qualitative


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Results: QualitativePart. Gender SCANPAD STRING

P01 M

MMBACCDEDCCCCDDEEBBBBBCBCDEDDE

EDDSWWRSSSSSSSSSSSSSSNSRWSSSSS

SSSWWSSMNSSDEEDCCDDDEFDDRSXWS

P02 F

MLAABBBBCCDDDDDDDEDEEDDDWWXSSR

RRSSSSSSSSWCDEEXWSXSSWXSSSSSSS

WSSSSSSSNSRDEBDDRSSSSSNNSSSRRM

MLRRNSSWXXXXWXDDEWSSSSSSNSNSSS

SWNSSSSS

P03 M

MMHBABBCDDCCDERWSSSSSXXIDEBBBBC

CCCDDDEESSSXXRSSSSSSSXDESRRWSSS

SNSSSSSSSD

P05 FMMLBCCCCDDDDEENXXWSSSSSSSSSSXW

RCDDCBCBBRSSSRSWWRMRLLIRRWWR

P06 FMMBBABBCDDDEEDEDEWWWWWXSSSSSS

SRSSSSSWSSSXXWSSWN

Scanpad String Similarities

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Results: Qualitative

COMPARING MAP READING ON PAPER AND DIGITAL MAPS

MASTER THESISANNELIES INCOUL


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Introduction

▪Paper versus digital maps▪Drawbacks of digital maps:

•Resolution•Colour ranges•Dimensions

▪Same information displayed differently▪Eye tracking

•Register the users’ eye movements (Point of Regards, POR)•Users’ cognitive process

compare the users’ attentive behaviour


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Study Design

▪Participants•32 Master students or researchers•Department of Geography, Ghent University•Similar domain knowledge in geography and cartography•Familiar with the design of the Belgian topographic maps

▪Stimuli•6 topographic maps on 1 : 10 000 •Regions in the Southern part of Belgium•Two similar groups of participants•Three paper and three digital maps (alternately)


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Study Design

▪Task•Visual search•Locate three labels in the map image•Questionnaire

-Background information-Familiarity with the depicted regions-Search strategy

▪Apparatus and Set-up•Eye tracker: SMI RED system 120Hz•50 inch television screen•Stand alone mode


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Methodology

▪Data selection•Calibration accuracy: < 1°•Tracking ratio: > 85%•Visual verification •Shift correction

Part. 1D 2P 3D 4P 5D 6P Part. 1P 2D 3P 4D 5P 6D

P01 x x x x x x P10 x x x x x


P07 x x x x P16 x x x x x x

P09 x x x x x x P18 x x x x x x


P13 x x x x x x P22 x x x x



P21 x x x x x P30 x x x x x x


P27 x x x x P34 x x x x x x


P33 x x x x x

TOT. 13 11 12 12 12 12 TOT. 10 10 11 11 12 12

- At least 10 individuals for each stimulus- In total: 25 participants- 68 paper and 70 digital stimuli


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Methodology

▪Creating the gridded visualisation•Areas Of Interest (AOIs)•Fixation counts and distribution•Grid of 32 x 22 cells•AOIs of 40 x 40 pixels


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Results


Mean search times(P = 0.956 > 0.05)

Fixations per second(P < 0.000)

Digital maps were less difficult to interpret than paper maps

Mean fixation duration(P = 0.210 > 0.05)

Shorter saccades digital maps

1

2

3

4

5

6

paper digital paper digital paper digital paper digital

1

2

3

4

5

6

Fixation count Fixation duration

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Conclusion & Future Work

▪Users’ attentive behaviour on paper and digital maps▪Controlled study design▪No unidirectional conclusions concerning efficiency▪Distribution of the fixations was similar

▪No real-life situations:•Generally, digital maps are presented on smaller screens

▪Further research, taking into account (digital maps):•Different screen sizes•Interaction tools•Specific design


INFLUENCE OF TOPONYMS’ COLOURS ON THEIR

READABILITY

PHD RESEARCHRASHA DEEB


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Research Context

▪Typography on maps•Semiotics according to Bertin•Bold, italic, shape (font), orientation, etc.

▪Preference?▪Efficiency?▪Lettering system?▪Colour?


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Research Questions

▪Influence of complementary colors (background-label) on the users’ search efficiency;

▪Is this further influenced by the user’s characteristics (gender and expertise)

▪Are the users’ preference and search efficiency linked?

▪The findings are compared to the ‘traditionally’ black labels


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Study Design

Color system

Design conditions Display conditions

HSV RGB CIE XYZ

Color No.

H° S% V% R G BL*

(D65)a*

(D65)b*

(D65)X Y Z

1 0, 100 100 255 0 0 69.9 95.7 77.5 76.09 40.18 4.617

2 30 100 100 255 128 0 86.0 48.6 79.7 88.28 67.98 11.92

3 60 100 100 255 255 0 121.8 -24.3 101.1 140.21 167.63 34.10

4 90 100 100 128 255 0 115.3 -90.6 90.3 81.46 145.01 33.79

5 120 100 100 0 255 0 112.3 -111.5 86.9 65.28 135.30 32.49

6 150 100 100 0 255 128 111.2 -99.6 40.6 68.50 131.85 76.55

7 180 100 100 0 255 255 116.5 -64.8 -39.4 98.45 149.03 257.74

8 210 100 100 0 128 255 70.6 20.4 -109.4 46.27 41.60 232.25

9 240 100 100 0 0 255 45.6 87.8 -148.7 33.45 14.97 222.16

10 270 100 100 128 0 255 55.5 94.3 -132.2 49.45 23.41 223.65

11 300 100 100 255 0 255 71.7 101.5 -6.3 83.62 43.21 52.4112 330 100 100 255 0 128 79.1 114.9 -92.2 109.63 55.10 225.46

Black 0 0 0 0 0 0 1.5 0.8 -5 0 0.2 0.2


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Study Design

31 participants 15 experts

- 7 females- 8 males

16 novices- 7 females- 9 males


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Results

Map Number

Black Color

F P

M SD M SD1 15.932 10.603 20.955 15.622 2.077 0.1552 20.252 21.420 13.672 10.090 2.217 0.1423 18.075 13.104 17.174 13.829 0.069 0.7934 14.972 22.713 17.785 14.344 0.319 0.5745 13.814 14.905 18.299 21.648 0.089 0.7666 23.342 198.80 32.562 38.221 1.328 0.2547 20.653 14.476 14.876 13.489 2.476 0.1228 14.511 12.934 14.822 13.136 0.009 0.9279 13.501 11.750 18.277 13.847 2.144 0.14810 16.589 12.404 20.589 12.404 1.300 0.25911 26.218 25.308 16.940 12.609 0.179 0.67412 14.560 10.138 35.918 38.613 8.314 0.006


Users’ responses (s) between black and colored labels (M= Mean, SD= Standard Deviation).

Source dfReaction Time(s)

Fixation Duration (s)

Fixation count (Fix/s)

F P F P F PCorrected Model 117 2.079 0.000 2.240 0.000 1.518 0.001

Intercept 1 354.591 0.000 535.231 0.0003343.52

00.000

Map number 23 4.519 0.000 2.756 0.000 1.930 0.000Expertise 1 1.361 0.244 0.055 0.814 0.185 0.667Gender 1 0.996 0.370 0.037 0.964 0.290 0.748Map number * Expertise 23 1.000 0.463 0.105 1.000 0.878 0.629Expertise * Gender 1 0.009 0.925 1.024 0.312 0.082 0.775Map number * Gender 44 1.037 0.410 0.244 1.000 0.679 0.944

Map number * Expertise * Gender

23 0.605 0.927 1.033 0.420 0.706 0.842

MANOVA tests Only map number (labels’ colour) significant

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Results

▪Colour differenceΔE*ab= {(ΔL*)2+(Δa*)2+(Δb*)2}1/2 where: ΔL*= L foreground* - L background*;

Δa*= a foreground* -a background*;

Δb*= b foreground* -b background*.


Colour difference vs. average fixation count per second

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Results

▪Luminance differenceΔY= Y foreground –Y background

calculated from the measured Y-value in the XYZ-system


luminance difference vs. the target fixation duration

MAPS, HOW DO USERS SEE THEM?

PHD & POSTDOC RESEARCH KRISTIEN OOMS


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Maps are … a medium to communicate

Research Aims:

How do map users

information on digital cartographic

products?

Read

Interpet

Store

Retrieve

Advice for design (syntax, semiotics)

of digital cartographic

products:

GuidelinesImplement in online

tools...

Optimise

Optimise


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Maps are … visual

Eye Tracking• Evaluate maps: UCD

- Log users’ Point of Regard∙ Location∙ Duration∙ …in screen-coordinates (px)

- Combination with other methods∙ Reaction time measurements∙ Thinking alound∙ Sketch maps∙ Questionnaires∙ …


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User studies

▪PhD ResearchBasic map design

®Expert vs. novices®Label placement

bo

rde

r-d

es

ign

tota

l-d

es

ign

ori

gin

al

vie

w

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User studies


▪PhD ResearchComplex map design

Expert vs novicesAdaptations in symbologyMirroring of map objects....

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Maps are … interactive

• ‘Maps on the Internet/Web’• Typical user interactions

- Panning- changing extent

- Zooming- changing scale & extent

• Influence on users’ cognitive processes?

Read

Interpet

Store

Retrieve

Benifical for user?e.g. memory, change blindness, …


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Eye Tracking & Interactivity?

▪Georeferencing eye movement dataChanging point of origin

Applying map projection formula

Spherical Mercator(inverse)


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Case Study

▪Three eye tracking systems•SMI RED 250•Tobii T120•SR Research EyeLink 1000

Panning


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Case Study

▪Three eye tracking systems


Panning

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Evaluation of panning in Google Maps

▪Alteration map - satellite view

▪Panning along a route•Zoom level 13

▪Find Belgium•Zoom level 7

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Future Work

▪Zooming?•In theory: same concept, only change in R value•Logging change in zoom levels

-Scroll wheel…

▪Other map projections?•In theory: same concept, only change in map projection formula•Example: Google Earth

-Spherical General Perspective Azimuthal projection


IN SEARCH OF INDOOR LANDMARKS

MASTER THESIS & PHD RESEARCHPEPIJN VIAENE


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Introduction

▪What is a landmark?= a wayfinding tool

a location or a direction view-action pair

▪How to identify a landmark?•Asking observerspicture based object recognition, verbal protocols, verbal eye-catcher detection, Wizard of Oz Prototyping, picture based object description ...

•Quantifying= object + saliency

» Visual – Semantic – Structural


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Study Design

thinking aloud[CTA]

[CRTA]

eye tracking[fixation locus]

[duration]


eye-mind hypothesissaliency = “eye catching”

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Study Design

[CTA (x2)]

[CRTA ]

▪13 recordings

▪1924 verbalisationsegments


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Study Design


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Results

41 % Referral to a landmark

59 % No referral to a landmark


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Results

= [59]≠ [73]Ø [89]

eye

trac

king

DP landmark category object landmark1 door (route) grey double door2 other / route indicator exhibition display3 route indicator sign (“Geography”)4 door (route) brown double door5 window window and view

6 door (route) / other pair of sticks / car batteries

7 door (route) brown doors with windows8 ornament big plant9 elevator red elevator10 poster wooden information board11 door (other) grey double door12 door (other) glass main entrance13 route indicator / other sign (“Paleontology”)14 door (other) brown double door15 window / route indicator window and view16 door (route) brown double door17 door (route) / poster single door

thin

king

alo

ud


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Conclusion

For the identification of (indoor) landmarkseye tracking can provide qualitative and complete data,

in addition verbal protocols can clarify specific fixations.


SOME FUTURE PLANS…


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Future Plans

▪Evaluation of the school’s textbooks

▪Evaluation of the new 25K symbology•Together with•1 : 20 000 1 : 25 000 •Paper maps, over whole Belgium


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Future Plans

▪Evaluation of Neogeography maps

▪Evaluation of maps on different devices•Touch-interactions


THANK YOU FOR YOUR ATTENTIONQUESTIONS?

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ogic - kristien ooms - eye tracking in the geo-domain: a perception on cartography, navigation and...

Data & Analytics

landscapewith wind turbines

visual impact of wind

resultaten wind turbine

landscape characteristics

landscape designresearch

type of landscape play

palack university olomouc1

longest viewings wind