Towards a Model for Predicting Intention in 3D Moving-Target Selection Tasks Oliver, James Casallas, Juan Oliver, James Kelly, Jonathan Merienne, Frederic Kelly, Jonathan Garbaya, Samir
dc.contributor.department Mechanical Engineering
dc.contributor.department Psychology 2018-02-15T20:04:23.000 2020-06-30T06:03:17Z 2020-06-30T06:03:17Z Tue Jan 01 00:00:00 UTC 2013 2014-01-01 2013-01-01
dc.description.abstract <p>Novel interaction techniques have been developed to address the difficulties of selecting moving targets. However, similar to their static-target counterparts, these techniques may suffer from clutter and overlap, which can be addressed by predicting intended targets. Unfortunately, current predictive techniques are tailored towards static-target selection. Thus, a novel approach for predicting user intention in movingtarget selection tasks using decision-trees constructed with the initial physical states of both the user and the targets is proposed. This approach is verified in a virtual reality application in which users must choose, and select between different moving targets. With two targets, this model is able to predict user choice with approximately 71% accuracy, which is significantly better than both chance and a frequentist approach.</p>
dc.description.comments <p>This is a manuscript of an article from Lecture Notes in Computer Science 8019 (2013): 13, doi: 10.1007/978-3-642-39360-0_2. Posted with permission. The final publication is available at Springer via <a href="" target="_blank"></a>.</p>
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dc.identifier archive/
dc.identifier.articleid 1135
dc.identifier.contextkey 6628831
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath me_pubs/131
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 19:44:17 UTC 2022
dc.source.uri 10.1007/978-3-642-39360-0_2
dc.subject.disciplines Computer-Aided Engineering and Design
dc.subject.disciplines Graphics and Human Computer Interfaces
dc.subject.keywords Department of Psychology
dc.subject.keywords Virtual Reality Application Center
dc.subject.keywords User intention
dc.subject.keywords prediction
dc.subject.keywords Fitts’ Law
dc.subject.keywords moving-target selection
dc.subject.keywords perceived difficulty
dc.subject.keywords decision trees
dc.subject.keywords virtual reality
dc.title Towards a Model for Predicting Intention in 3D Moving-Target Selection Tasks
dc.type article
dc.type.genre article
dspace.entity.type Publication
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