Atsutada Nakatsuji

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2ranked-venue papers

1as first author

0since 2021 · last 2006

—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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.

Artificial intelligence 1 paper		3D vision · 100%
Computer graphics and multimedia 1 paper		Geometric modeling and processing · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Computer vision › 3D vision 3d reconstruction	0.1	1	2006	Stabilizing the Focal Length Computation for 3-D Reconstruction from Two Uncalibrated Views · Int. J. Comput. Vis. 2006
Computer vision › 3D vision › camera calibration focal length estimation	0.1	1	2006	Stabilizing the Focal Length Computation for 3-D Reconstruction from Two Uncalibrated Views · Int. J. Comput. Vis. 2006
Computer vision › 3D vision structure from motion	0.1	1	2006	Stabilizing the Focal Length Computation for 3-D Reconstruction from Two Uncalibrated Views · Int. J. Comput. Vis. 2006
Geometric modeling and processing › mesh processing mesh optimization	0.1	1	2005	Mesh Optimization Using an Inconsistency Detection Template · ICCV 2005
Geometric modeling and processing › solid modeling polyhedral scene representation	0.1	1	2005	Mesh Optimization Using an Inconsistency Detection Template · ICCV 2005

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

inconsistency detection template · 0.1

Year	Publication	Venue	Position
2006	Stabilizing the Focal Length Computation for 3-D Reconstruction from Two Uncalibrated Views Kenichi Kanatani, Atsutada Nakatsuji, Yasuyuki Sugaya	Int. J. Comput. Vis.	2
2005	Mesh Optimization Using an Inconsistency Detection Template abstract We propose a new technique for optimizing a triangular mesh for polyhedral representation of the scene in a video stream. We introduce a specially designed template that can effectively detect color and texture discontinuities. Using real images, we demonstrate that our method is superior to existing methods. Atsutada Nakatsuji, Yasuyuki Sugaya, Kenichi Kanatani	ICCV	1