Predicting Stereoscopic Viewing Comfort Using a Coherence-Based Computational Model

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dc.contributor.authorRichardt, Christianen_US
dc.contributor.authorSwirski, Lechen_US
dc.contributor.authorDavies, Ian P.en_US
dc.contributor.authorDodgson, Neil A.en_US
dc.contributor.editorDouglas Cunningham and Tobias Isenbergen_US
dc.date.accessioned2013-10-22T07:15:16Z
dc.date.available2013-10-22T07:15:16Z
dc.date.issued2011en_US
dc.description.abstractWe introduce a novel computational model for objectively assessing the visual comfort of stereoscopic 3D imagery. Our model integrates research in visual perception with tools from stereo computer vision to quantify the degree of stereo coherence between both stereo half-images. We show that the coherence scores computed by our model strongly correlate with human comfort ratings using a perceptual study of 20 participants rating 80 images each. Based on our experiments, we further propose a taxonomy of stereo coherence issues which affect viewing comfort, and propose a set of computational tools that extend our model to identify and localise stereo coherence issues from stereoscopic 3D images.en_US
dc.description.seriesinformationComputational Aesthetics in Graphics, Visualization, and Imagingen_US
dc.identifier.isbn978-1-4503-0908-0en_US
dc.identifier.issn1816-0859en_US
dc.identifier.urihttps://doi.org/10.2312/COMPAESTH/COMPAESTH11/097-104en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.2.10 [Artificial Intelligence]: Vision and Scene Understanding-Perceptual reasoning; I.4.8 [Image Processing]: Scene Analysis-Depth cues & stereoen_US
dc.titlePredicting Stereoscopic Viewing Comfort Using a Coherence-Based Computational Modelen_US
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CompAesth 11: Workshop on Computational Aesthetics