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The BOXEL framework for 2.5D data with applications to virtual drivethroughs and ray tracing
Nir Goldschmidt,
Dan Gordon
Department of Computer Science
Research output
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Contribution to journal
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Article
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peer-review
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Dive into the research topics of 'The BOXEL framework for 2.5D data with applications to virtual drivethroughs and ray tracing'. Together they form a unique fingerprint.
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Keyphrases
Antichain
100%
Ray Tracing
100%
2.5D Data
100%
Disjoint
14%
Rectangle
14%
Total Order
14%
Urban Environment
14%
Parallelizing
14%
Efficient Implementation
14%
Disjoint Set
14%
Ordered Sequences
14%
Natural Scenes
14%
Run-length Encoding
14%
Multi-core Machines
14%
Non-intersecting
14%
Simple Modification
14%
Backorder
14%
Bounding Volume
14%
Real-time Rendering
14%
Occluder
14%
Expected Runtime
14%
Computer Science
ray-tracing
100%
Speed-up
33%
Efficient Implementation
33%
Urban Environment
33%
Run Length Encoding
33%
Multicore
33%
Bounding Volume
33%
Expected Runtime
33%
Mathematics
Antichain
100%
Total Order
14%
Intersects
14%
Disjoint Set
14%
Run-Length Encoding
14%
Simple Modification
14%
Realtime Rendering
14%
Earth and Planetary Sciences
Real Time
100%