Stochastic models of gaze-shifts
One point that is not addressed by the great majority of computational models is the "noisy", idiosyncratic variation of the random exploration exhibited by different observers when viewing the same scene, or even by the
same subject along different trials.
Such variations speak of stochastic nature of scanpaths - the succession of gaze-shifts - , which is particularly evident for those resulting from saccadic eye movements
The problem: how random are gaze-shifts?
Eye-tracked scanpaths of different subjects
looking at the same emotional expression
Eye-tracked scanpaths of different subjects
looking at the same video (CNRS dataset)
This research work was initially inspired by seminal work of Prof. Larry Stark, Telerobotics and Neurology Units, University of California Berkeley.
This research has been carried on with Prof. Mario Ferraro (University of Torino)
A research (non random) walk
Random walk
Brownian Random walk
Levy Random walk
The Foraging
metaphor
Constrained
Levy search
Levy
Hybrid
Montecarlo
Composite
walks
Active
random
sampling
Alpha-stable
distributions
Motor behavior
Simple
composite
search
Physica A
(2004)
Euvip
(2010)
ICIAP
(2011)
Gaze-shift mechanisms can be conceived as a motor program implementation of an active random sampling strategy that the Human Visual System has evolved in order to efficiently and effectively infer properties of the surrounding world
Gaze-shifts are generated by an underlying stochastic process.
If observed gaze-shifts are generated by an underlying stochastic process the distribution functions and the temporal dynamics of eye movements should be completely specified by the stochastic process
Working assumptions
Euvip
(2011)
