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Patrick Guidotti

dblp:79/6217 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2013
0000-0002-6817-2584ORCID · corroborated

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

Graphics, computer vision, multimedia, augmented reality and games · 3 · 1 first-authorHuman-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
2 papers
Rendering · 100%

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

TopicWeightPapersLastEvidence papers
Rendering
point-based rendering
0.122004
Confetti: Object-Space Point Blending and Splatting · IEEE Trans. Vis. Comput. Graph. 2004
Object-space point blending and splatting · SIGGRAPH 2003
Rendering › volume rendering
splatting
0.012003
Object-space point blending and splatting · SIGGRAPH 2003
Rendering
GPU rendering
0.012004
Confetti: Object-Space Point Blending and Splatting · IEEE Trans. Vis. Comput. Graph. 2004

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

alpha blending · 0.1texture mapping · 0.0covariance matrix · 0.0transformation-invariant covariance matrix · 0.0alpha-texture mapping · 0.0
YearPublicationVenuePosition
2013 Image Restoration with a New Class of Forward-Backward-Forward Diffusion Equations of Perona-Malik Type with Applications to Satellite Image Enhancement
abstract
A new class of anisotropic diffusion models is proposed for image processing which can be viewed either as a novel kind of regularization of the classical Perona--Malik model or, as advocated by the authors, as a new independent model. The models are diffusive in nature and are characterized by the presence of both forward and backward regimes. In contrast to the Perona--Malik model, in the proposed model the backward regime is confined to a bounded region, and gradients are only allowed to grow up to a large but tunable size, thus effectively preventing indiscriminate singularity formation, i.e., staircasing. Extensive numerical experiments demonstrate that the method is a viable denoising/deblurring tool. The method is significantly faster than competing state-of-the-art methods and appears to be particularly effective for simultaneous denoising and deblurring. An application to satellite image enhancement is also presented.
Patrick Guidotti, James V. Lambers
SIAM J. Imaging Sci.1
2004 Confetti: Object-Space Point Blending and Splatting
abstract
In this paper, we present Confetti, a novel point-based rendering approach based on object-space point interpolation of densely sampled surfaces. We introduce the concept of a transformation-invariant covariance matrix of a set of points which can efficiently be used to determine splat sizes in a multiresolution point hierarchy. We also analyze continuous point interpolation in object-space and we define a new class of parameterized blending kernels as well as a normalization procedure to achieve smooth blending. Furthermore, we present a hardware accelerated rendering algorithm based on texture mapping and alpha-blending as well as programmable vertex and pixel-shaders.
Renato Pajarola, Miguel Sainz, Patrick Guidotti
IEEE Trans. Vis. Comput. Graph.3
2003 Object-space point blending and splatting
abstract
We present a novel point-based rendering approach based on object-space point interpolation. We introduce the concept of a transformation-invariant covariance matrix of a set of points to efficiently determine splat sizes in a multiresolution hierarchy. We analyze continuous point interpolation in object-space, and define a new class of parametrized blending kernels to achieve smooth blending. Furthermore, we present a hardware accelerated rendering algorithm based on α-texture mapping and α-blending.
Renato Pajarola, Miguel Sainz, Patrick Guidotti
SIGGRAPH3