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Thomas Saunders

dblp:129/8564 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 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.

Artificial intelligence
1 paper
3D vision · 100%
Computer graphics and multimedia
1 paper
Computer animation and physical simulation · 77% Geometric modeling and processing · 23%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
shape from shading
0.212013
Water Surface Modeling from a Single Viewpoint Video · IEEE Trans. Vis. Comput. Graph. 2013
Computer vision › 3D vision › 3d reconstruction › surface reconstruction
water surface reconstruction
0.212013
Water Surface Modeling from a Single Viewpoint Video · IEEE Trans. Vis. Comput. Graph. 2013
Computer animation and physical simulation
fluid simulation
0.212013
Water Surface Modeling from a Single Viewpoint Video · IEEE Trans. Vis. Comput. Graph. 2013
Geometric modeling and processing
surface reconstruction
0.012013
Water Surface Modeling from a Single Viewpoint Video · IEEE Trans. Vis. Comput. Graph. 2013

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

shape-from-shading · 0.3shallow water model · 0.3
YearPublicationVenuePosition
2013 Water Surface Modeling from a Single Viewpoint Video
abstract
We introduce a video-based approach for producing water surface models. Recent advances in this field output high-quality results but require dedicated capturing devices and only work in limited conditions. In contrast, our method achieves a good tradeoff between the visual quality and the production cost: It automatically produces a visually plausible animation using a single viewpoint video as the input. Our approach is based on two discoveries: first, shape from shading (SFS) is adequate to capture the appearance and dynamic behavior of the example water; second, shallow water model can be used to estimate a velocity field that produces complex surface dynamics. We will provide qualitative evaluation of our method and demonstrate its good performance across a wide range of scenes.
Chuan Li 0001, David Pickup, Thomas Saunders, Darren Cosker, David Marshall 0001, Peter Hall 0001, Philip J. Willis
IEEE Trans. Vis. Comput. Graph.3