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David Berrios

dblp:88/10701 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 2Human-computer interaction and ubiquitous computing · 1

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
Geometric modeling and processing · 56% Rendering · 44%

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

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › shape analysis
curvature estimation
0.112012
Real-Time GPU Surface Curvature Estimation on Deforming Meshes and Volumetric Data Sets · IEEE Trans. Vis. Comput. Graph. 2012
Rendering
real-time rendering
0.112012
Real-Time GPU Surface Curvature Estimation on Deforming Meshes and Volumetric Data Sets · IEEE Trans. Vis. Comput. Graph. 2012
Geometric modeling and processing › deformable models
deformable mesh
0.012012
Real-Time GPU Surface Curvature Estimation on Deforming Meshes and Volumetric Data Sets · IEEE Trans. Vis. Comput. Graph. 2012

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

ambient occlusion approximation · 0.1GPU algorithm · 0.1CUDA · 0.1
YearPublicationVenuePosition
2012 Real-Time GPU Surface Curvature Estimation on Deforming Meshes and Volumetric Data Sets
abstract
Surface curvature is used in a number of areas in computer graphics, including texture synthesis and shape representation, mesh simplification, surface modeling, and nonphotorealistic line drawing. Most real-time applications must estimate curvature on a triangular mesh. This estimation has been limited to CPU algorithms, forcing object geometry to reside in main memory. However, as more computational work is done directly on the GPU, it is increasingly common for object geometry to exist only in GPU memory. Examples include vertex skinned animations and isosurfaces from GPU-based surface reconstruction algorithms. For static models, curvature can be precomputed and CPU algorithms are a reasonable choice. For deforming models where the geometry only resides on the GPU, transferring the deformed mesh back to the CPU limits performance. We introduce a GPU algorithm for estimating curvature in real time on arbitrary triangular meshes. We demonstrate our algorithm with curvature-based NPR feature lines and a curvature-based approximation for an ambient occlusion. We show curvature computation on volumetric data sets with a GPU isosurface extraction algorithm and vertex-skinned animations. We present a graphics pipeline and CUDA implementation. Our curvature estimation is up to ~18x faster than a multithreaded CPU benchmark.
Wesley Griffin, Yu Wang 0028, David Berrios, Marc Olano
IEEE Trans. Vis. Comput. Graph.3
2011 GPU curvature estimation on deformable meshes
abstract
Surface curvature is used in a number of areas in computer graphics, including texture synthesis and shape representation, mesh simplification, surface modeling, and non-photorealistic line drawing. Most real-time applications must estimate curvature on a triangular mesh. This estimation has been limited to CPU algorithms, forcing object geometry to reside in main memory. However, as more computational work is done directly on the GPU, it is increasingly common for object geometry to exist only in GPU memory. Examples include vertex skinned animations and isosurfaces from GPU-based surface reconstruction algorithms.
Wesley Griffin, Yu Wang 0028, David Berrios, Marc Olano
SI3D3