Simulating gaze behavior of virtual crowds by predicting interest points

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buir.advisorGüdükbay, Uğur
dc.contributor.authorAğıl, Umut
dc.date.accessioned2016-08-26T11:48:21Z
dc.date.available2016-08-26T11:48:21Z
dc.date.copyright2016-07
dc.date.issued2016-07
dc.date.submitted2016-08-23
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2016.en_US
dc.descriptionIncludes bibliographical references (leaves 50-55).en_US
dc.description.abstractCreating realistic crowd behavior is one of the major goals in crowd simulations. Simulating gaze behavior and predicting interest points of virtual characters play a signifficant role in creating believable scenes, however this aspect has not received much attention in the field. This study proposes a saliency model, which enables virtual agents to produce gaze behavior. The model measures the effects of distinct pre-deffined saliency features that are implemented by examining the state-of-the-art perception studies. When predicting an agent's interest point, we compute the saliency scores by using a weighted sum function for other agents and environment objects in the field of view of the agent for each frame. Then we determine the most salient entity in the virtual scene according to the viewer agent by comparing the scores. We execute this process for each agent in the scene, thus agents gain a visual understanding about their environment. Besides, our model introduces new aspects to crowd perception, such as perceiving characters as groups of people, gaze copy phenomena and effects of agent velocity on attention. For evaluation, we compare the resulting saliency gaze model with real world crowd behavior in captured videos. In the experiments, we simulate the gaze behavior in real crowds. The results show that the proposed approach generates plausible gaze behaviors and is easily adaptable to varying scenarios for virtual crowds.en_US
dc.description.degreeM.S.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2016-08-26T11:48:21Z No. of bitstreams: 1 10122407.pdf: 28411561 bytes, checksum: ea0517c1bfe78a813c5cfcb97478c0e1 (MD5)en
dc.description.provenanceMade available in DSpace on 2016-08-26T11:48:21Z (GMT). No. of bitstreams: 1 10122407.pdf: 28411561 bytes, checksum: ea0517c1bfe78a813c5cfcb97478c0e1 (MD5) Previous issue date: 2016-08en
dc.description.statementofresponsibilityby Umut Ağıl.en_US
dc.format.extentxi, 55 leaves : illustrations (some color)en_US
dc.identifier.itemidB153994
dc.identifier.urihttp://hdl.handle.net/11693/32168
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCrowd simulationen_US
dc.subjectSaliencyen_US
dc.subjectGaze behavioren_US
dc.subjectPerceptionen_US
dc.subjectInterest point detectionen_US
dc.subjectGaze copyen_US
dc.titleSimulating gaze behavior of virtual crowds by predicting interest pointsen_US
dc.title.alternativeİlgi noktalarını tahmin ederek sanal kalabalıklar için bakış davranışı simülasyonuen_US
dc.typeThesisen_US

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Dept. of Computer Engineering - Master's degree