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Antonio Carlos dos Santos Souza

dblp:139/8768 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author

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 · 87% Virtual and augmented reality · 13%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
GPUs and heterogeneous computing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › shape registration
non-rigid surface registration
0.212015
A GPU-based adaptive algorithm for non-rigid surface registration · VR 2015
Geometric modeling and processing › shape registration
surface registration
0.212015
A GPU-based adaptive algorithm for non-rigid surface registration · VR 2015
Virtual and augmented reality › augmented reality
markerless augmented reality
0.112015
A GPU-based adaptive algorithm for non-rigid surface registration · VR 2015
GPUs and heterogeneous computing › GPU computing
GPU algorithms
0.112015
A GPU-based adaptive algorithm for non-rigid surface registration · VR 2015

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

adaptive algorithm · 0.4GPU parallelism · 0.4
YearPublicationVenuePosition
2015 A GPU-based adaptive algorithm for non-rigid surface registration
abstract
Non-rigid surface registration is fundamental when accurate tracking or reconstruction of 3D deformable shapes is desirable. However, the majority of non-rigid registration methods are not as fast as the ones developed in the field of rigid registration. Fast methods for non-rigid surface registration are particularly interesting for markerless augmented reality applications, in which the object being used as marker can support non-rigid user interaction. In this paper, we present an adaptive algorithm for non-rigid surface registration. Taking advantage from this adaptivity and the parallelism of the GPU, we show that the proposed algorithm is capable to achieve near real-time performance with an approach as accurate as the ones proposed in the literature.
Antonio Carlos dos Santos Souza, Márcio C. F. Macedo, Antônio L. Apolinário Jr.
VR1