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Charles J. Pisula

dblp:09/1163 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none

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

Artificial intelligence and machine learning · 1Graphics, 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.

Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%
Artificial intelligence
1 paper
Information extraction and text analysis · 100%

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

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis
document analysis
0.112005
Conformal Deskewing of Non-Planar Documents · CVPR (1) 2005
Geometric modeling and processing › surface parameterization
conformal mapping
0.112005
Conformal Deskewing of Non-Planar Documents · CVPR (1) 2005
Geometric modeling and processing
surface parameterization
0.112005
Conformal Deskewing of Non-Planar Documents · CVPR (1) 2005

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

conformal mapping · 0.1
YearPublicationVenuePosition
2005 Conformal Deskewing of Non-Planar Documents
abstract
This paper presents an approach that uses conformal mapping to parameterize a document's 3D shape to a 2D plane. Using this conformal parametrization, a restorative mapping between an image of the distorted document and a "flattened" representation of the document can be computed and used to deskew the image. Our experiments show that arbitrarily distorted documents can be restored to within a single pixel of their true planar format. In addition, surface points can be constrained to map to specified locations in the restored 2D plane.
Michael S. Brown, Charles J. Pisula
CVPR (1)2