When searching for a target within an image, our brain can adopt
different strategies, but which one does it choose? This question can be
answered by tracking the motion of the eye while it executes the task.
Following many individuals performing various search tasks, we
distinguish between two competing strategies. Motivated by these
findings, we introduce a model that captures the interplay of the search
strategies and allows us to create artificial eye-tracking trajectories,
which could be compared with the experimental ones. Identifying the
model parameters allows us to quantify the strategy employed in terms of
ensemble averages, characterizing each experimental cohort. In this way,
we can discern with high sensitivity the relation between the visual
landscape and the average strategy, disclosing how small variations in
the image induce changes in the strategy.
%0 Journal Article
%1 WOS:000406663400020
%A Amor, Tatiana A
%A Lukovic, Mirko
%A Herrmann, Hans J
%A Jr., Jose S Andrade
%C 6-9 CARLTON HOUSE TERRACE, LONDON SW1Y 5AG, ENGLAND
%D 2017
%I ROYAL SOC
%J JOURNAL OF THE ROYAL SOCIETY INTERFACE
%K eye movement; search search; strategies} {visual
%N 132
%R 10.1098/rsif.2017.0406
%T Influence of scene structure and content on visual search strategies
%V 14
%X When searching for a target within an image, our brain can adopt
different strategies, but which one does it choose? This question can be
answered by tracking the motion of the eye while it executes the task.
Following many individuals performing various search tasks, we
distinguish between two competing strategies. Motivated by these
findings, we introduce a model that captures the interplay of the search
strategies and allows us to create artificial eye-tracking trajectories,
which could be compared with the experimental ones. Identifying the
model parameters allows us to quantify the strategy employed in terms of
ensemble averages, characterizing each experimental cohort. In this way,
we can discern with high sensitivity the relation between the visual
landscape and the average strategy, disclosing how small variations in
the image induce changes in the strategy.
@article{WOS:000406663400020,
abstract = {When searching for a target within an image, our brain can adopt
different strategies, but which one does it choose? This question can be
answered by tracking the motion of the eye while it executes the task.
Following many individuals performing various search tasks, we
distinguish between two competing strategies. Motivated by these
findings, we introduce a model that captures the interplay of the search
strategies and allows us to create artificial eye-tracking trajectories,
which could be compared with the experimental ones. Identifying the
model parameters allows us to quantify the strategy employed in terms of
ensemble averages, characterizing each experimental cohort. In this way,
we can discern with high sensitivity the relation between the visual
landscape and the average strategy, disclosing how small variations in
the image induce changes in the strategy.},
added-at = {2022-05-23T20:00:14.000+0200},
address = {6-9 CARLTON HOUSE TERRACE, LONDON SW1Y 5AG, ENGLAND},
author = {Amor, Tatiana A and Lukovic, Mirko and Herrmann, Hans J and Jr., Jose S Andrade},
biburl = {https://www.bibsonomy.org/bibtex/21e444e62e09dd445eb2e469f63e1b9a0/ppgfis_ufc_br},
doi = {10.1098/rsif.2017.0406},
interhash = {ce7bd1a2f14b2a1abe9ae53bf4d8085c},
intrahash = {1e444e62e09dd445eb2e469f63e1b9a0},
issn = {1742-5689},
journal = {JOURNAL OF THE ROYAL SOCIETY INTERFACE},
keywords = {eye movement; search search; strategies} {visual},
number = 132,
publisher = {ROYAL SOC},
pubstate = {published},
timestamp = {2022-05-23T20:00:14.000+0200},
title = {Influence of scene structure and content on visual search strategies},
tppubtype = {article},
volume = 14,
year = 2017
}