Open AccessInferring Intent and Action from Gaze in Naturalistic Behavior
Author(s) -
Kristian Lukander,
Miika Toivanen,
Kai Puolamäki
Publication year - 2017
Publication title -
international journal of mobile human computer interaction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 17
eISSN - 1942-3918
pISSN - 1942-390X
DOI - 10.4018/ijmhci.2017100104
Subject(s) - gaze , action (physics) , computer science , inference , task (project management) , human–computer interaction , focus (optics) , artificial intelligence , cognitive psychology , wearable computer , psychology , optics , management , embedded system , quantum mechanics , physics , economics
Weconstantlymoveourgazetogatheracutevisualinformationfromourenvironment.Conversely,as originallyshownbyYarbusinhisseminalwork,theelicitedgazepatternsholdinformationoverour changingattentionalfocuswhileperformingatask.Recently,theproliferationofmachinelearning algorithmshasallowedtheresearchcommunitytotesttheideaofinferring,orevenpredictingaction andintentfromgazebehaviour.Theon-goingminiaturizationofgazetrackingtechnologiestoward pervasivewearablesolutionsallowsstudyinginferencealsoineverydayactivitiesoutsideresearch laboratories.Thispaperscopestheemergingfieldandreviewsstudiesfocusingontheinferenceof intentandactioninnaturalisticbehaviour.Whilethetask-specificnatureofgazebehavior,andthe variabilityinnaturalisticsetupspresentchallenges,gaze-basedinferenceholdsaclearpromisefor machine-basedunderstandingofhumanintentandfutureinteractivesolutions. KeywoRdS Eye Movements, Gaze Tracking, Inference, Intent Modeling, Scoping Study, Task Modeling
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