PathlinesExplorer — Image-based exploration of large-scale pathline fields

Handle URI:
http://hdl.handle.net/10754/605228
Title:
PathlinesExplorer — Image-based exploration of large-scale pathline fields
Authors:
Nagoor, Omniah H.; Hadwiger, Markus ( 0000-0003-1239-4871 ) ; Srinivasan, Madhusudhanan
Abstract:
PathlinesExplorer is a novel image-based tool, which has been designed to visualize large scale pathline fields on a single computer [7]. PathlinesExplorer integrates explorable images (EI) technique [4] with order-independent transparency (OIT) method [2]. What makes this method different is that it allows users to handle large data on a single workstation. Although it is a view-dependent method, PathlinesExplorer combines both exploration and modification of visual aspects without re-accessing the original huge data. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathline segments. With this view-dependent method, it is possible to filter, color-code, and explore large-scale flow data in real-time. In addition, optimization techniques such as early-ray termination and deferred shading are applied, which further improves the performance and scalability of our approach.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program; Visualization Laboratory
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 IEEE Scientific Visualization Conference (SciVis)
Conference/Event name:
2015 IEEE Scientific Visualization Conference (SciVis)
Issue Date:
25-Oct-2015
DOI:
10.1109/SciVis.2015.7429512
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7429512
Appears in Collections:
Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorNagoor, Omniah H.en
dc.contributor.authorHadwiger, Markusen
dc.contributor.authorSrinivasan, Madhusudhananen
dc.date.accessioned2016-04-14T09:15:31Zen
dc.date.available2016-04-14T09:15:31Zen
dc.date.issued2015-10-25en
dc.identifier.doi10.1109/SciVis.2015.7429512en
dc.identifier.urihttp://hdl.handle.net/10754/605228en
dc.description.abstractPathlinesExplorer is a novel image-based tool, which has been designed to visualize large scale pathline fields on a single computer [7]. PathlinesExplorer integrates explorable images (EI) technique [4] with order-independent transparency (OIT) method [2]. What makes this method different is that it allows users to handle large data on a single workstation. Although it is a view-dependent method, PathlinesExplorer combines both exploration and modification of visual aspects without re-accessing the original huge data. Our approach is based on constructing a per-pixel linked list data structure in which each pixel contains a list of pathline segments. With this view-dependent method, it is possible to filter, color-code, and explore large-scale flow data in real-time. In addition, optimization techniques such as early-ray termination and deferred shading are applied, which further improves the performance and scalability of our approach.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7429512en
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectImage-based renderingen
dc.subjectdeferred shadingen
dc.subjectearly-ray terminationen
dc.subjectexplorable imagesen
dc.subjectpathline fieldsen
dc.subjectper-pixel linked listen
dc.titlePathlinesExplorer — Image-based exploration of large-scale pathline fieldsen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.contributor.departmentVisualization Laboratoryen
dc.identifier.journal2015 IEEE Scientific Visualization Conference (SciVis)en
dc.conference.date25-30 Oct. 2015en
dc.conference.name2015 IEEE Scientific Visualization Conference (SciVis)en
dc.conference.locationChicago, ILen
dc.eprint.versionPost-printen
kaust.authorNagoor, Omniah H.en
kaust.authorHadwiger, Markusen
kaust.authorSrinivasan, Madhusudhananen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.