Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Santanu Bose

dblp:16/445 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 1994
—ORCID · none

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

Artificial intelligence and machine learning · 2Graphics, 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
2 papers
3D vision · 100%
Theoretical computer science
1 paper
Computational geometry · 100%
Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%

Topics — the 3 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
object pose estimation
0.011994
A New Generalized Computational Framework for Finding Object Orientation Using Perspective Trihedral Angle Constraint · IEEE Trans. Pattern Anal. Mach. Intell. 1994
Computer vision › 3D vision › camera pose estimation
perspective pose estimation
0.011993
Shape from perspective trihedral angle constraint · CVPR 1993
Computer vision › 3D vision
pose estimation
0.011993
Shape from perspective trihedral angle constraint · CVPR 1993

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

closed-form solution · 0.0trihedral angle constraint · 0.0angle-to-angle correspondence · 0.0inverse perspective projection · 0.0
YearPublicationVenuePosition
1994 A New Generalized Computational Framework for Finding Object Orientation Using Perspective Trihedral Angle Constraint
abstract
This paper investigates a fundamental problem of determining the position and orientation of a three-dimensional (3-D) object using a single perspective image view. The technique is focused on the interpretation of trihedral angle constraint information. A new closed form solution based on Kanatani's formulation is proposed. The main distinguishing feature of the authors' method over the original Kanatani formulation is that their approach gives an effective closed form solution for a general trihedral angle constraint. The method also provides a general analytic technique for dealing with a class of problem of shape from inverse perspective projection by using "angle to angle correspondence information." A detailed implementation of the authors' technique is presented. Different trihedral angle configurations were generated using synthetic data for testing the authors' approach of finding object orientation by angle to angle constraint. The authors performed simulation experiments by adding some noise to the synthetic data for evaluating the effectiveness of their method in a real situation. It has been found that the authors' method worked effectively in a noisy environment which confirms that the method is robust in practical application.>
Yuyan Wu, S. Sitharama Iyengar, Ramesh Jain 0001, Santanu Bose
IEEE Trans. Pattern Anal. Mach. Intell.4
1993 Shape from perspective trihedral angle constraint
abstract
A fundamental problem of determining the position and orientation of a 3-D object using a single perspective image view is defined and investigated. The technique is based on the interpretation of trihedral angle constraint information. A new closed-form solution to the problem is proposed. The method also provides a general analytic technique for dealing with a class of problem of shape from inverse perspective projection by using angle to angle correspondence information. Simulation experiments show that the authors' method is effective and robust for real application.>
Yuyan Wu, S. Sitharama Iyengar, Ramesh Jain 0001, Santanu Bose
CVPR4