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Adam Pospísil

dblp:232/9008 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 44% Image and video coding · 44% Rendering · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › 3d scene compression
volumetric data compression
0.512021
QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets · IEEE Trans. Vis. Comput. Graph. 2021
Visualization and visual analytics
volume visualization
0.512021
QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets · IEEE Trans. Vis. Comput. Graph. 2021
Rendering › volume rendering
direct volume rendering
0.112021
QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets · IEEE Trans. Vis. Comput. Graph. 2021

Methods — techniques the papers use, named apart from their topics

vertical stack encoding · 0.5quadtree compression · 0.5
YearPublicationVenuePosition
2021 Spatio-temporal BRDF: Modeling and synthesis
Daniel Meister 0002, Adam Pospísil, Imari Sato, Jirí Bittner
Comput. Graph.2
2021 QuadStack: An Efficient Representation and Direct Rendering of Layered Datasets
abstract
We introduce QuadStack, a novel algorithm for volumetric data compression and direct rendering. Our algorithm exploits the data redundancy often found in layered datasets which are common in science and engineering fields such as geology, biology, mechanical engineering, medicine, etc. QuadStack first compresses the volumetric data into vertical stacks which are then compressed into a quadtree that identifies and represents the layered structures at the internal nodes. The associated data (color, material, density, etc.) and shape of these layer structures are decoupled and encoded independently, leading to high compression rates (4× to 54× of the original voxel model memory footprint in our experiments). We also introduce an algorithm for value retrieving from the QuadStack representation and we show that the access has logarithmic complexity. Because of the fast access, QuadStack is suitable for efficient data representation and direct rendering. We show that our GPU implementation performs comparably in speed with the state-of-the-art algorithms (18-79 MRays/s in our implementation), while maintaining a significantly smaller memory footprint.
Alejandro Graciano, Antonio J. Rueda Ruiz, Adam Pospísil, Jirí Bittner, Bedrich Benes
IEEE Trans. Vis. Comput. Graph.3
2019 Ray Classification for Accelerated BVH Traversal
abstract
Abstract For ray tracing based methods, traversing a hierarchical acceleration data structure takes up a substantial portion of the total rendering time. We propose an additional data structure which cuts off large parts of the hierarchical traversal. We use the idea of ray classification combined with the hierarchical scene representation provided by a bounding volume hierarchy. We precompute short arrays of indices to subtrees inside the hierarchy and use them to initiate the traversal for a given ray class. This arrangement is compact enough to be cache‐friendly, preventing the method from negating its traversal gains by excessive memory traffic. The method is easy to use with existing renderers which we demonstrate by integrating it to the PBRT renderer. The proposed technique reduces the number of traversal steps by 42% on average, saving around 15% of time of finding ray‐scene intersection on average.
J. Hendrich, Adam Pospísil, Daniel Meister 0002, Jirí Bittner
Comput. Graph. Forum2