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Spatial Analysis of Eye Movements!
Spatial Analysis
n Heat Maps (Attention Maps)!n Area of Interest (AOI) Analysis!
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Heat Maps!
Image
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Fixations Overlaid
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Gridded Heat Maps
n Gridded Heat Map!¨ Divide image into matrix of cells. Brightness of each
cell proportional to:!n Number of fixations!n Total fixation duration!
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Gridded Heat Map
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Smoothed Heat Maps
n Convolve fixation map with a Gaussian, i.e. for each fixation add a 2D-Gaussian centered at that location!
n Width of Gaussian is arbitrary. We can use functional field of view (e.g. σ=2°), but there are no good guidelines.!
n Amplitude of Gaussian: 1 or proportional to fixation duration !
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Smooth Heat Map
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Heat Map
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Effect of Gaussian Width σ
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σ=20 σ=5
Heat Map
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Using Woodford’s SC package
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3D Heat Map
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Limitations of Heat Maps
n Heat maps represent distribution of fixations, but not more!
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Central Bias n Participants have a tendency to fixate the center
screen.!n Compute global fixation distribution over all
experimental conditions.!
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Statistical Analysis!
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Statistical Analysis
n By smoothing fixations, heat map values at nearby locations are highly correlated. Statistical problem similar to that of fMRI!
n Using Random Field Theory!n Using Bootstrapping!
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Bootstrapping n Method!
¨ Create random samples (with replacement) from a distribution and compare to empirical fixation distribution (e.g. in a particular experimental condition)!
¨ Sampling from Uniform distribution, Gaussian distribution, empirical global fixation distribution!
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iMap3
19 Gaussian-smoothed heat maps
Caldara, R., & Miellet, S. (2011). iMap: A Novel Method for Statistical Fixation Mapping of Eye Movement data. Behavior Research Methods, 43(3), 864-78
iMap3 n The t-test maps are enhanced
using threshold-free cluster enhancement (FCE), which takes amplitude and extent of signal into account!
n To compensate for multiple comparisons, test using bootstrap!
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Saliency Maps!
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Saliency Analysis Saliency analyses processes information in a number of channels that are sensitive to changes in different image characteristics (intensity, color, orientation).!!Information in these channels are combined into a single saliency map, which indicates “interesting” points in any of these component maps.!!To what extent can saliency explain fixation distributions? !!
Saliency Toolbox
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http://www.saliencytoolbox.net/
Characteristics of Fixated Locations
n Tatler, Baddeley & Gilchrist (2005)!
n Characterize lumincance, chromaticity, contrast, and edge content of images.!
n Compare fixated with non-fixated areas.!
n Fixated areas tend to be more distinctive in high spatial frequencies!
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Heat Maps and Saliency
n Correlation-based Measures!¨ Compute correlation between smoothed heat maps
and saliency map!
n Kullback-Leibler Divergence!¨ Measure of overall dissimilarity of two probability
distributions!
n ROC Analysis!
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KL(H,S) = sk loghijsiji, j
∑
Heat Maps and Saliency n Le Meur & Baccino (2012) Methods for comparing scanpaths and
saliency maps, Behavior Research Methods, 45, 251-266.!
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Fixation Analysis Software (for Windows)
Area of Interest Analysis!
Fixations Overlaid
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Region Map
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AOI Area Normalization
n With uniform distribution of fixation across image, number of fixations in an AOI is proportional to AOI area!
n Solution: Divide number of fixations by AOI area to obtain number of fixations per unit area in each AOI!
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Central Bias Effect
n Possible Solution!¨ Compute overall fixation map averaged over all
experimental conditions!¨ Interpret deviations from the overall fixation map !
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Content Bias
n Two AOIs with the same area may have different or more complex content, such that dwell time is longer for one than the other.!
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Creating your own AOIs
n Many eye tracking systems (e.g. Eyelink, ASL, Dikablis) come with software for defining areas of interest!
n Alternatively, use a Paint program!
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Dynamic AOI Analysis!
Dynamic AOIs
n Egomotion: Head and body movements!¨ Many modern eye trackers deal with egomotion within
limits!
n Problems with!¨ Large scale egomotion!¨ Object motion!
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Dynamic AOIs
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Keyframing
n Frame-by-Frame Coding is extremely time-consuming!
n Use of keyframing!
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keyframing in 3ds Max for size and path interpolation
Motion & Eye Tracking
n Combine eye tracking with tracking of head, body and objects.!
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Demo and Exercises!