GEO DATA MANAGEMENT Dr. Kristien Ooms; Ghent University - - PowerPoint PPT Presentation

▶
geo data
SMART_READER_LITE
LIVE PREVIEW

GEO DATA MANAGEMENT Dr. Kristien Ooms; Ghent University - - PowerPoint PPT Presentation

Jan 30, 2023 408 likes •1.29k views

EYE TRACKING IN GEO DATA MANAGEMENT Dr. Kristien Ooms; Ghent University Kristien.Ooms@UGent.be Time Type Trial L POR X [px] L POR Y [px] 15256356851 SMP 1 589,64 590,82 W HAT IS EYE TRACKING ? 15256365267 SMP 1 586,6 587,1

slide-1
SLIDE 1

EYE TRACKING IN GEO DATA MANAGEMENT

  • Dr. Kristien Ooms; Ghent University

Kristien.Ooms@UGent.be

slide-2
SLIDE 2

2

▪ Tracking the user’s eye movements

  • Sampling rate (times/second)
  • Current location of eyes on screen/picture/etc.
  • (x,y,t) → ‘raw data’

▪ Metrics and measurements

  • Deriving meaningful metrics from raw data
  • fixations, saccades, smooth pursuit

▪ Study design?

  • Medium: paper, screen, etc. ?
  • Topic: VR, websites, simulators, maps, etc.
  • Analysis: qualitative, quantitative, visual, statistical, etc.

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

Time Type Trial L POR X [px] L POR Y [px] 15256356851 SMP 1 589,64 590,82 15256365267 SMP 1 586,6 587,1 15256373592 SMP 1 824,04 396,63 15256390210 SMP 1 589,08 584,7 15256398588 SMP 1 592,91 580,93 15256406933 SMP 1 588,32 578,83 15256423568 SMP 1 594,35 580,26 15256431942 SMP 1 594,57 579,7 15256440305 SMP 1 598,26 575,05 15256448557 SMP 1 598,33 571,11 15256456954 SMP 1 597,96 569,4 15256465310 SMP 1 597,92 571,55 15256481930 SMP 1 600,35 570,2 15256490314 SMP 1 601,55 571,8 15256498681 SMP 1 603,14 568,78

slide-3
SLIDE 3

4

… A LITTLE BIT OF HISTORY

▪ Earliest research: 1880 – 1920

  • Basis facts about eye movement discovered

▪ Phase with more applied focus, little research

  • Buswell: “How people look at pictures” (1935)
  • Tinker (1946)
  • Cannot learn much from eye tracking data
  • Limits of technology
  • Fits et. al (1950)
  • Study eye movements of pilots in cockpit
  • First use in usability engineering

▪ Clear visualization of eye movements

  • Yarbus (1967)
  • Shows importance of eye movement recordings

Eye Tracking for GeoDataManagement - Kristien Ooms

Yarbus (1967)

Source: http://psych.wfu.edu/art_ schirillo/articles/Buswell,%201935.pdf

slide-4
SLIDE 4

5

… A LITTLE BIT OF HISTORY

▪ Recent evolution

  • 1970s:
  • Improvements in eye movement recording systems
  • Advances in psychological theory
  • 1980s:

 Use of eye tracking in real time

  • Human-Computer interaction
  • Disabled users
  • 1990s

 Solving usability problems

  • Internet, websites, emails, video-conferencing, …

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-5
SLIDE 5

6

▪ Video-based combined pupil and corneal reflection

  • Gives ‘point of regard’ (POR) measurements!
  • Point where user is looking
  • Gaze position
  • Pixel coordinates – screen coordinates
  • Corneal reflections (from infra-red light source)
  • Purkinje reflections or images
  • Eye rotations: relative positional difference with pupil center
  • Appropriate callibration: determining user’s POR

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

slide-6
SLIDE 6

7

▪ Video-based combined pupil and corneal reflection

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

slide-7
SLIDE 7

8

▪ Measurements:

  • Points Of Regard at certain sampling rate
  • Calibration!
  • x, y: screen coordinates
  • Timestamp
  • Huge amount of ‘raw data’
  • Deriving metrics:
  • Fixations, Saccades, (Smooth Pursuit)

DESIGNING AND CONDUCTING USER RESEARCH

… DEMO …

slide-8
SLIDE 8

9

▪ Metrics:

  • Fixations
  • Stable relative position pupil – corneal reflection

 dispersion = ??? (40px; 0.5° visual angle; …)

  • During certain period

minimum duration = ??? (80 – 150 ms)

  • Saccades:
  • Rapid eye movements
  • Reposition of fovea
  • Person does not ‘see’ anything during saccade

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

slide-9
SLIDE 9

10

▪ Metrics → meaning?

  • Link eye movements - attentive behavior
  • Can shift attention without movement of the eyes!
  • Central and peripheral vision
  • Attention precedes a saccade to a certain location
  • Complex task  link is very tight
  • Need of peripheral vision
  • Need of attention

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

slide-10
SLIDE 10

11

▪ Metrics → meaning?

  • Link eye movements - attentive behavior
  • Data Interpretation

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

“Information processing is guided by higher level mental processes. When we construct our perception drawing on our past experiences and expectations” “The most basic sensation and perception. Entry Level” sensory analysis”

slide-11
SLIDE 11

12

▪ References:

  • Book of
  • Holmqvist et al. (2011)
  • Duchowski et al. (2007)
  • Jacob & Karn (2003)
  • 20 different usability studies
  • Most commonly used metrics:

∙ Number of fixations, overall ∙ Gaze % (proportion of time) on each of the AOIs ∙ Fixation duration mean, overall ∙ Number of fixations on each of the AOI ∙ Gaze duration mean, on each of the AOI ∙ Fixation rate,overall (fixation/saccades)

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

slide-12
SLIDE 12

13

  • Related to Fixations (Overview by Poole & Ball, 2005)

Eye Tracking for GeoDataManagement - Kristien Ooms

WHAT IS EYE TRACKING?

slide-13
SLIDE 13

14

▪ Related to Saccades (Overview by Poole & Ball, 2005)

Eye Tracking for GeoDataManagement - Kristien Ooms

METRICS & MEANING

slide-14
SLIDE 14

15

▪ Other methods

  • Qualitative vs. Quantitative
  • Questionnaires
  • Thinking aloud
  • Response time measurements
  • Sketching
  • Scoring
  • Mouse & keyboard logging
  • Observation
  • Interview
  • EEG
  • …

Eye Tracking for GeoDataManagement - Kristien Ooms

STUDY DESIGN

slide-15
SLIDE 15

16

  • Software
  • Setting up experiment
  • Recording data
  • Interpretation ‘raw’ data
  • Analyses
  • Vendor specific
  • Open Source
  • Statistical Packages
  • Spatial analyses

Eye Tracking for GeoDataManagement - Kristien Ooms

STUDY DESIGN

slide-16
SLIDE 16

EYE TRACKING AT THE DEPARTMENT OF GEOGRAPHY, GHENT UNIVERSITY

  • PROF. DR. PHILIPPE DE MAEYER
  • PROF. DR. NICO VAN DE WEGHE
  • PROF. DR. VEERLE VAN EETVELDE
  • DR. KRISTIEN OOMS
  • DR. RASHA DEEB

LIEN DUPONT ANNELIES INCOUL PEPIJN VIAENE LIESELOT LAPON …

slide-17
SLIDE 17

18

LANDSCAPE PERCEPTION

Which elements in a landscape catch the attention and in which context are they most eye-catching? Important for the location of new infrastructures Observer Representation Landscape

Observations of landscapes are influenced by…

Eye Tracking for GeoDataManagement - Kristien Ooms Lien Dupont

slide-18
SLIDE 18

19

LANDSCAPE PERCEPTION

  • How 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?

Experiment 1 Experiment 2 Experiment 3

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-19
SLIDE 19

20

LANDSCAPE PERCEPTION

  • Study Design Experiment 1

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)

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-20
SLIDE 20

21

Open Semi-open Enclosed

Homogeneous Heterogeneous

21 landscape expert participants 90 photographs in total 23 novice participants

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-21
SLIDE 21

22

LANDSCAPE PERCEPTION

  • 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

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-22
SLIDE 22

23

LANDSCAPE PERCEPTION

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

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-23
SLIDE 23

24 Eye Tracking for GeoDataManagement - Kristien Ooms

LANDSCAPE PERCEPTION

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

slide-24
SLIDE 24

25

1050 x 1680 matrices

Correlation between focus maps and saliency maps?

Saliency map Focus map

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-25
SLIDE 25

26

INFLUENCE OF WIND TURBINES?

▪ 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?

Eye Tracking for GeoDataManagement - Kristien Ooms Fanny Van Den Haute

slide-26
SLIDE 26

27

INFLUENCE OF WIND TURBINES?

▪ Stimuli

  • Panoramic photos
  • Simulations in photoshop
  • 5 different landscape types
  • 60 pictures in total
  • 7 seconds free viewing
  • Participants
  • 15 experts
  • 29 non-experts

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-27
SLIDE 27

28

INFLUENCE OF WIND TURBINES?

▪ Wind turbine

  • Time to first fixation
  • % longest viewings
  • Number of fixations
  • Fixation durations

▪ Wind turbine vs. other vertical objects ▪ Simulation of wind turbines in same landscape ▪ Experts vs. non-experts ▪ Type of landscape

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-28
SLIDE 28

29

INFLUENCE OF WIND TURBINES?

 WIND TURBINES HAVE A VISUAL IMPACT  EXPERTISE HAS NO INFLUENCE ON VIEWING PATTERN  TYPE OF LANDSCAPE HAS INFLUENCE ON VIEWING PATTERN

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-29
SLIDE 29

30

Evaluate added value of the Triangular Model to depict time intervals, compared to the ‘traditional’ Linear Model

Eye Tracking for GeoDataManagement - Kristien Ooms

EFFICIENCY OF THE TRIANGULAR MODEL?

Pieter Laseure

slide-30
SLIDE 30

31

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

Eye Tracking for GeoDataManagement - Kristien Ooms

EFFICIENCY OF THE TRIANGULAR MODEL?

slide-31
SLIDE 31

32 Students’ response time Students’ nr of fixations per second

GROUP nr

  • AVG. SCORE

LM

  • AVG. SCORE

TM PREFERENCE

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 models Students’ fixation duration Students’ saccadic length Students’ score Eye Tracking for GeoDataManagement - Kristien Ooms

EFFICIENCY OF THE TRIANGULAR MODEL?

slide-32
SLIDE 32

33 Eye Tracking for GeoDataManagement - Kristien Ooms

EFFICIENCY OF THE TRIANGULAR MODEL?

slide-33
SLIDE 33

34

Part. Gender SCANPAD STRING P01 M MMBACCDEDCCCCDDEEBBBBBCBCDEDDE EDDSWWRSSSSSSSSSSSSSSNSRWSSSSS SSSWWSSMNSSDEEDCCDDDEFDDRSXWS P02 F MLAABBBBCCDDDDDDDEDEEDDDWWXSSR RRSSSSSSSSWCDEEXWSXSSWXSSSSSSS WSSSSSSSNSRDEBDDRSSSSSNNSSSRRM MLRRNSSWXXXXWXDDEWSSSSSSNSNSSS SWNSSSSS P03 M MMHBABBCDDCCDERWSSSSSXXIDEBBBBC CCCDDDEESSSXXRSSSSSSSXDESRRWSSS SNSSSSSSSD P05 F MMLBCCCCDDDDEENXXWSSSSSSSSSSXW RCDDCBCBBRSSSRSWWRMRLLIRRWWR P06 F MMBBABBCDDDEEDEDEWWWWWXSSSSSS SRSSSSSWSSSXXWSSWN

Scanpad String Similarities Eye Tracking for GeoDataManagement - Kristien Ooms

EFFICIENCY OF THE TRIANGULAR MODEL?

slide-34
SLIDE 34

35 Eye Tracking for GeoDataManagement - Kristien Ooms

EFFICIENCY OF THE TRIANGULAR MODEL?

slide-35
SLIDE 35

36

▪ 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

Eye Tracking for GeoDataManagement - Kristien Ooms

READING PAPER VS. DIGITAL MAPS

Annelies Incoul

slide-36
SLIDE 36

37

READING PAPER VS. DIGITAL MAPS

▪ 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)

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-37
SLIDE 37

38

READING PAPER VS. DIGITAL MAPS

▪ 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

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-38
SLIDE 38

39

READING PAPER VS. DIGITAL MAPS

▪ Creating the gridded visualisation

  • Areas Of Interest (AOIs)
  • Fixation counts and distribution
  • Grid of 32 x 22 cells
  • AOIs of 40 x 40 pixels

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-39
SLIDE 39

40 Eye Tracking for GeoDataManagement - Kristien Ooms

READING PAPER VS. DIGITAL MAPS

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

slide-40
SLIDE 40

41

DESIGN OF MAP LABELS

▪ Typography on maps

  • Semiotics according to Bertin
  • Bold, italic, shape (font), orientation, etc.

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

Eye Tracking for GeoDataManagement - Kristien Ooms Rasha Deeb

slide-41
SLIDE 41

42

DESIGN OF MAP LABELS

▪ Research Questions

  • Influence of complementary colors (background-label)
  • n 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

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-42
SLIDE 42

43

DESIGN OF MAP LABELS

31 participants 15 experts

  • 7 females
  • 8 males

16 novices

  • 7 females
  • 9 males

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-43
SLIDE 43

44

STUDY DESIGN

Color system Design conditions Display conditions HSV RGB CIE XYZ Color No. H° S% V% R G B L* (D65) a* (D65) b* (D65) X Y Z 1 0, 100 100 255 69.9 95.7 77.5 76.09 40.18 4.617 2 30 100 100 255 128 86.0 48.6 79.7 88.28 67.98 11.92 3 60 100 100 255 255 121.8

  • 24.3

101.1 140.21 167.63 34.10 4 90 100 100 128 255 115.3

  • 90.6

90.3 81.46 145.01 33.79 5 120 100 100 255 112.3

  • 111.5

86.9 65.28 135.30 32.49 6 150 100 100 255 128 111.2

  • 99.6

40.6 68.50 131.85 76.55 7 180 100 100 255 255 116.5

  • 64.8
  • 39.4

98.45 149.03 257.74 8 210 100 100 128 255 70.6 20.4

  • 109.4

46.27 41.60 232.25 9 240 100 100 255 45.6 87.8

  • 148.7

33.45 14.97 222.16 10 270 100 100 128 255 55.5 94.3

  • 132.2

49.45 23.41 223.65 11 300 100 100 255 255 71.7 101.5

  • 6.3

83.62 43.21 52.41 12 330 100 100 255 128 79.1 114.9

  • 92.2

109.63 55.10 225.46 Black 1.5 0.8

  • 5

0.2 0.2

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-44
SLIDE 44

45

DESIGN OF MAP LABELS

▪ Colour difference

ΔE*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

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-45
SLIDE 45

46

DESIGN OF MAP LABELS

▪ Luminance difference

ΔY= Y foreground –Y background

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

luminance difference vs. the target fixation duration

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-46
SLIDE 46

47

LANDMARKS IN INDOOR NAVIGATION

▪ What is a landmark?

= a wayfinding tool

 a location or a direction  view-action pair

▪ How to identify a landmark?

  • Asking observers

picture based object recognition, verbal protocols, verbal eye-catcher detection, Wizard of Oz Prototyping, picture based object description ...

  • Quantifying

= object + saliency

» Visual – Semantic – Structural Eye Tracking for GeoDataManagement - Kristien Ooms Pepijn Viaene

slide-47
SLIDE 47

48

LANDMARKS IN INDOOR NAVIGATION

▪ Study Aim & Design

thinking aloud [CTA] [CRTA] eye tracking [fixation locus] [duration]

eye-mind hypothesis saliency = “eye catching”

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-48
SLIDE 48

49

LANDMARKS IN INDOOR NAVIGATION

[CTA (x2)] [CRTA ] ▪ 13 recordings ▪ 1924 verbalisation segments

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-49
SLIDE 49

50

LANDMARKS IN INDOOR NAVIGATION

[CTA (x2)] [CRTA ] ▪ 13 recordings

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-50
SLIDE 50

51 Eye Tracking for GeoDataManagement - Kristien Ooms

LANDMARKS IN INDOOR NAVIGATION

▪ Analysing the eye tracking data

slide-51
SLIDE 51

52

LANDMARKS IN INDOOR NAVIGATION

▪ Results

41 % Referral to a landmark 59 % No referral to a landmark

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-52
SLIDE 52

53

LANDMARKS IN INDOOR NAVIGATION

▪ Conclusions:

For the identification of (indoor) landmarks eye tracking can provide qualitative and complete data, in addition verbal protocols can clarify specific fixations.

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-53
SLIDE 53

54

MAPS, HOW DO USERS SEE THEM?

Research Aims:

How do map users information on digital cartographic products?

Read Interpet Store Retrieve

Advice for design (syntax, semiotics)

  • f digital

cartographic products: Guidelines Implement in online tools ...

Eye Tracking for GeoDataManagement - Kristien Ooms Kristien Ooms

slide-54
SLIDE 54

55 Eye Tracking for GeoDataManagement - Kristien Ooms

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

∙ …

slide-55
SLIDE 55

56 Eye Tracking for GeoDataManagement - Kristien Ooms

PHD RESEARCH

Basic map design

Expert vs. novices Label placement

border- design total- design

  • riginal

view

slide-56
SLIDE 56

57 Eye Tracking for GeoDataManagement - Kristien Ooms

PHD RESEARCH

Complex map design

Expert vs novices Adaptations in symbology Mirroring of map objects ....

slide-57
SLIDE 57

58

PHD RESEARCH

▪ 3D gridded visualisation

Average total fixation duration Average fixation duration per fixation

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-58
SLIDE 58

59

PHD RESEARCH

▪ Gridded visualisation: statistical comparison

Statistical comparison (ANOVA)

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-59
SLIDE 59

60

PHD RESEARCH

▪ Scanpaths

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-60
SLIDE 60

61

PHD RESEARCH

▪ Thinking aloud

  • Word segmentation (count in ‰)

Based on theme  Based on frequency  Eye Tracking for GeoDataManagement - Kristien Ooms

slide-61
SLIDE 61

62

PHD RESEARCH

▪ Thinking aloud

  • ‘Full thought’
  • 4 Levels of codes:

Level 1: Map Level Orientate – Execute - Evaluate Level 2: Item Level Gather Thougts – Draw – Correct - Evaluate Level 3: Confidence Confident – Neutral – Not Confident Level 4: Actions

Check – Correct – Draw – Erase – Fill Colour – Talk – Take Pencil

  • Time ratio for each code: [0-1]

Psychological Theories Task Analysis Psychological Model Proposed Codes Coding Scheme Segmented Protocols Transcriptions

(Raw Protocols)

Coded Protocols

T H E O R Y USER DATA

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-62
SLIDE 62

63

PHD RESEARCH

▪ Sketch maps

  • Order of drawing
  • Scores on maps
  • Questionnaire
  • Stated confidence

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-63
SLIDE 63

64

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, …

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-64
SLIDE 64

65

EYE TRACKING & INTERACTIVITY?

▪ Level of experimental control…

  • High: simulations of interactions

 same stimuli  high comparability  easy to analyse

  • Low: free interactions

 different stimuli  low comparability  difficult to analyse

At certain timestamp:

  • different scale
  • different extent

…for each participant  Less intrusion on cognitive processes  Higher realism

… vs. ecological validity

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-65
SLIDE 65

66

LOGGING INTERACTIVITY?

▪ Mouse actions

  • Mouse down – Mouse up – Scroll wheel
  • Time stamp & location (x and y in px)
  • Eye Tracking software
  • Existing tools
  • APIs web mapping software
  • Javascript, AJAX, PHP, SQL, DB (with proxy server)
  • Desktop tool

 based on JAVA: JNativeHook  based on Python: PyHook

Panning Zooming

slide-66
SLIDE 66

67

EYE TRACKING & INTERACTIVITY?

▪ Georeferencing eye movement data

Changing point of

  • rigin

Applying map projection formula

Spherical Mercator (inverse) 𝜇 = 𝜇0 + 𝑦 𝑆 𝜒 = 2 𝑢𝑏𝑜−1 𝑓𝑦𝑞 𝑧 𝑆 − 𝜌 2

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-67
SLIDE 67

68

EYE TRACKING & INTERACTIVITY?

▪ Three eye tracking systems

  • SMI RED 250
  • Tobii T120
  • SR Research EyeLink 1000

Panning

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-68
SLIDE 68

69

EYE TRACKING & INTERACTIVITY?

▪ Three eye tracking systems

Panning

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-69
SLIDE 69

70

PANNING IN GOOGLE MAPS

▪ Panning along a route

  • Count intersections
  • Zoom level 13
  • Alteration map - satellite view

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-70
SLIDE 70

71

PANNING IN GOOGLE MAPS

▪ Find Belgium

  • Zoom level 7
  • Alteration map - satellite view

Start: Fiji Start: Quttinirpaaq NP Canada Eye Tracking for GeoDataManagement - Kristien Ooms

slide-71
SLIDE 71

72 Eye Tracking for GeoDataManagement - Kristien Ooms

PANNING IN GOOGLE MAPS

slide-72
SLIDE 72

73

PANNING IN GOOGLE MAPS

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-73
SLIDE 73

74

PANNING IN GOOGLE MAPS

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-74
SLIDE 74

75 Eye Tracking for GeoDataManagement - Kristien Ooms

PANNING IN GOOGLE MAPS

SpaCoast SpaAarlon Fiji-Belgium Canada-Belgium

mouse key down mouse key up

slide-75
SLIDE 75

76

RESULTS

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-76
SLIDE 76

77

RESULTS

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-77
SLIDE 77

78

SIDE PROJECT: THE EYE TRIBE TRACKER

▪ Small-size & Low cost

Easy transportable

Use outside lab Do parallel tests

▪ Low cost = low accuracy, precision, reliability???

  • Compare with SMI RED 250

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-78
SLIDE 78

79

SIDE PROJECT: THE EYE TRIBE TRACKER

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-79
SLIDE 79

80

SIDE PROJECT: THE EYE TRIBE TRACKER

Eye Tracking for GeoDataManagement - Kristien Ooms

  • Eye Tracking device
  • Sampling Rate
  • Recording software
  • Processing software
slide-80
SLIDE 80

81

SIDE PROJECT: THE EYE TRIBE TRACKER

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-81
SLIDE 81

82

SIDE PROJECT: THE EYE TRIBE TRACKER

Eye Tracking for GeoDataManagement - Kristien Ooms

Time interval (ms) SMI 60Hz (%) ET 60 Hz (%) 15 0.012265 0.010027 16 0.042248 42.00816 17 99.82965 45.10662 [18-20] 0.014991 8.259242 ]20-30] ]30-40] 0 4.532389 >40 0.100849 0.083562

Recorded time intervals between samples at 60 Hz 60 Hz = once every 16.666…ms dist distX distY M Med SD M Med SD M Med SD ET 274 46 440

  • 97
  • 5

343

  • 152
  • 0,69

344 SMI 57 44 69

  • 10
  • 6

68 12 11 56 Med-test .280 .594 .000 Mann-Whitney U test .000 .030 .000 Statistical comparison of the registered offset values

slide-82
SLIDE 82

83

FUTURE PLANS

▪ 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

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-83
SLIDE 83

84

FUTURE PLANS

▪ Evaluation of Neogeography maps ▪ Evaluation of maps on different devices

  • Touch-interactions

▪ Interdisciplinary Project

  • Marketing Department

Eye Tracking for GeoDataManagement - Kristien Ooms Lieselot Lapon

slide-84
SLIDE 84

85

FUTURE PLANS

▪ Evaluation of the school’s textbooks ▪ Use of landmarks in pedestrian navigation systems

  • Indoor vs. outdoor
  • Urban vs. rural

▪ Evaluation of the new 25K symbology

  • Together with
  • 1 : 20 000  1 : 25 000
  • Paper maps, over whole Belgium

Eye Tracking for GeoDataManagement - Kristien Ooms

slide-85
SLIDE 85

86

  • Mail me: Kristien.Ooms@UGent.be
  • Have a look at the website of

ICA Commission

  • n Use, Users, and Usability Issues

 http://cartogis.ugent.be/kooms/UUI/

  • Bibliography
  • Resources of past events
  • Upcoming events:
  • AAG Special Sessions on Cognition, Visualization, and User Issues, US
  • Training Workshop on ‘Designing and Conducting User Studies’ in conjunction

with the ICC+GIS, Bulgaria

  • Join the mailing list to stay up-to-date

Eye Tracking for GeoDataManagement - Kristien Ooms

WANT TO KNOW MORE?

slide-86
SLIDE 86

EYE TRACKING IN GEO DATA MANAGEMENT

  • Dr. Kristien Ooms; Ghent University

Kristien.Ooms@UGent.be