Predicting eye movements in multiple object tracking using neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081740%3A_____%2F16%3A00466857" target="_blank" >RIV/68081740:_____/16:00466857 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/16:10336704
Result on the web
<a href="http://dx.doi.org/10.1145/2857491.2857502" target="_blank" >http://dx.doi.org/10.1145/2857491.2857502</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2857491.2857502" target="_blank" >10.1145/2857491.2857502</a>
Alternative languages
Result language
angličtina
Original language name
Predicting eye movements in multiple object tracking using neural networks
Original language description
In typical Multiple Object Tracking (MOT) paradigm, the participant's task is to track targets amongst distractors for several seconds. Understanding gaze strategies in MOT can help us reveal attentional mechanisms in dynamic tasks. Previous attempts relied on analytical strategies (such as averaging object positions). An alternative approach is to find this relationship using machine learning technique. After preprocessing, we assembled a dataset with 48,000 datapoints, representing 1534 MOT trials or 2.5 hours. In this study, we used feedforward neural networks to predict gaze position and compared predicted gaze with analytical strategies from previous studies using median distance. Our results showed that neural networks were able to predict eye positions better than current strategies. Particularly, they performed better when we trained the network with all objects, not targets only. It supports the hypothesis that people are influenced by distractor positions during tracking.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
AN - Psychology
OECD FORD branch
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Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Eye Tracking Research and Applications Symposium (ETRA)
ISBN
978-145034125-7
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
271-274
Publisher name
Association for Computing Machinery
Place of publication
Charleston
Event location
Charleston
Event date
Mar 14, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000389809700045