Temporal Coherence Predictor for Time Varying Volume Data Based on Perceptual Functions

dc.contributor.authorNoonan, Tomen_US
dc.contributor.authorCampoalegre, Lazaroen_US
dc.contributor.authorDingliana, Johnen_US
dc.contributor.editorDavid Bommes and Tobias Ritschel and Thomas Schultzen_US
dc.date.accessioned2015-10-07T05:13:32Z
dc.date.available2015-10-07T05:13:32Z
dc.date.issued2015en_US
dc.description.abstractThis paper introduces an empirical, perceptually-based method which exploits the temporal coherence in consecutive frames to reduce the CPU-GPU traffic size during real-time visualization of time-varying volume data. In this new scheme, a multi-threaded CPU mechanism simulates GPU pre-rendering functions to characterize the local behaviour of the volume. These functions exploit the temporal coherence in the data to reduce the sending of complete per frame datasets to the GPU. These predictive computations are designed to be simple enough to be run in parallel on the CPU while improving the general performance of GPU rendering. Tests performed provide evidence that we are able to reduce considerably the texture size transferred at each frame without losing visual quality while maintaining performance compared to the sending of entire frames to the GPU. The proposed framework is designed to be scalable to Client/Server network based implementations to deal with multi-user systems.en_US
dc.description.sectionheadersVisualizationen_US
dc.description.seriesinformationVision, Modeling & Visualizationen_US
dc.identifier.doi10.2312/vmv.20151255en_US
dc.identifier.isbn978-3-905674-95-8en_US
dc.identifier.pages33-40en_US
dc.identifier.urihttps://doi.org/10.2312/vmv.20151255en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectTimeen_US
dc.subjectvarying dataen_US
dc.subjectParallel Processing Volume Renderingen_US
dc.titleTemporal Coherence Predictor for Time Varying Volume Data Based on Perceptual Functionsen_US
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