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Thomas Bonfort

dblp:58/5230 · DBLP profile ↗
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3ranked-venue papers
2as 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 · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 2 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%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
3d reconstruction
0.012003
Voxel Carving for Specular Surfaces · ICCV 2003
Computer vision › 3D vision › 3d shape reconstruction
specular surface reconstruction
0.012003
Voxel Carving for Specular Surfaces · ICCV 2003
Computer vision › 3D vision › 3d shape reconstruction
voxel carving
0.012003
Voxel Carving for Specular Surfaces · ICCV 2003

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

surface normal consistency · 0.0calibrated camera · 0.0
YearPublicationVenuePosition
2006 General Specular Surface Triangulation
Thomas Bonfort, Peter F. Sturm, Pau Gargallo
ACCV (2)1
2006 How to Compute the Pose of an Object Without a Direct View?
Peter F. Sturm, Thomas Bonfort
ACCV (2)2
2003 Voxel Carving for Specular Surfaces
abstract
We present an novel algorithm that reconstructs voxels of a general 3D specular surface from multiple images of a calibrated camera. A calibrated scene (i.e. points whose 3D coordinates are known) is reflected by the unknown specular surface onto the image plane of the camera. For every viewpoint, surface normals are associated to the voxels traversed by each projection ray formed by the reflection of a scene point. A decision process then discards voxels whose associated surface normals are not consistent with one another. The output of the algorithm is a collection of voxels and surface normals in 3D space, whose quality and size depend on user-set thresholds. The method has been tested on synthetic and real images. Visual and quantified experimental results are presented.
Thomas Bonfort, Peter F. Sturm
ICCV1