Clustered deep shadow maps for integrated polyhedral and volume rendering

Handle URI:
http://hdl.handle.net/10754/564494
Title:
Clustered deep shadow maps for integrated polyhedral and volume rendering
Authors:
Bornik, Alexander; Knecht, Wolfgang; Hadwiger, Markus ( 0000-0003-1239-4871 ) ; Schmalstieg, Dieter
Abstract:
This paper presents a hardware-accelerated approach for shadow computation in scenes containing both complex volumetric objects and polyhedral models. Our system is the first hardware accelerated complete implementation of deep shadow maps, which unifies the computation of volumetric and geometric shadows. Up to now such unified computation was limited to software-only rendering . Previous hardware accelerated techniques can handle only geometric or only volumetric scenes - both resulting in the loss of important properties of the original concept. Our approach supports interactive rendering of polyhedrally bounded volumetric objects on the GPU based on ray casting. The ray casting can be conveniently used for both the shadow map computation and the rendering. We show how anti-aliased high-quality shadows are feasible in scenes composed of multiple overlapping translucent objects, and how sparse scenes can be handled efficiently using clustered deep shadow maps. © 2012 Springer-Verlag.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program; Visual Computing Center (VCC)
Publisher:
Springer Science + Business Media
Journal:
Lecture Notes in Computer Science
Conference/Event name:
8th International Symposium on Visual Computing, ISVC 2012
Issue Date:
2012
DOI:
10.1007/978-3-642-33179-4_31
Type:
Conference Paper
ISSN:
03029743
ISBN:
9783642331787
Appears in Collections:
Conference Papers; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorBornik, Alexanderen
dc.contributor.authorKnecht, Wolfgangen
dc.contributor.authorHadwiger, Markusen
dc.contributor.authorSchmalstieg, Dieteren
dc.date.accessioned2015-08-04T07:02:26Zen
dc.date.available2015-08-04T07:02:26Zen
dc.date.issued2012en
dc.identifier.isbn9783642331787en
dc.identifier.issn03029743en
dc.identifier.doi10.1007/978-3-642-33179-4_31en
dc.identifier.urihttp://hdl.handle.net/10754/564494en
dc.description.abstractThis paper presents a hardware-accelerated approach for shadow computation in scenes containing both complex volumetric objects and polyhedral models. Our system is the first hardware accelerated complete implementation of deep shadow maps, which unifies the computation of volumetric and geometric shadows. Up to now such unified computation was limited to software-only rendering . Previous hardware accelerated techniques can handle only geometric or only volumetric scenes - both resulting in the loss of important properties of the original concept. Our approach supports interactive rendering of polyhedrally bounded volumetric objects on the GPU based on ray casting. The ray casting can be conveniently used for both the shadow map computation and the rendering. We show how anti-aliased high-quality shadows are feasible in scenes composed of multiple overlapping translucent objects, and how sparse scenes can be handled efficiently using clustered deep shadow maps. © 2012 Springer-Verlag.en
dc.publisherSpringer Science + Business Mediaen
dc.titleClustered deep shadow maps for integrated polyhedral and volume renderingen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalLecture Notes in Computer Scienceen
dc.conference.date16 July 2012 through 18 July 2012en
dc.conference.name8th International Symposium on Visual Computing, ISVC 2012en
dc.conference.locationRethymnon, Creteen
dc.contributor.institutionLudwig Boltzmann Institute, Clinical-Forensic Imaging (CFI), Graz, Austriaen
dc.contributor.institutionVienna University of Technology, Vienna, Austriaen
dc.contributor.institutionGraz University of Technology, Graz, Austriaen
kaust.authorHadwiger, Markusen
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