Details
| Original language | English |
|---|---|
| Pages (from-to) | 414-427 |
| Number of pages | 14 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 3021 |
| Publication status | Published - 2004 |
| Externally published | Yes |
Abstract
In this contribution we present an approach for 2D-3D pose estimation of 3D free-form surface models. In our scenario we observe a free-form object in an image of a calibrated camera. Pose estimation means to estimate the relative position and orientation of the 3D object to the reference camera system. The object itself is modeled as a twoparametric 3D surface and extended by one-parametric contour parts of the object. A twist representation, which is equivalent to a Fourier representation allows for a low-pass approximation of the object model, which is advantageously applied to regularize the pose problem. The experiments show, that our developed algorithms are fast (200ms/frame) and accurate (1° rotational error/frame).
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 3021, 2004, p. 414-427.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Pose estimation of free-form objects
AU - Rosenhahn, Bodo
AU - Sommer, Gerald
PY - 2004
Y1 - 2004
N2 - In this contribution we present an approach for 2D-3D pose estimation of 3D free-form surface models. In our scenario we observe a free-form object in an image of a calibrated camera. Pose estimation means to estimate the relative position and orientation of the 3D object to the reference camera system. The object itself is modeled as a twoparametric 3D surface and extended by one-parametric contour parts of the object. A twist representation, which is equivalent to a Fourier representation allows for a low-pass approximation of the object model, which is advantageously applied to regularize the pose problem. The experiments show, that our developed algorithms are fast (200ms/frame) and accurate (1° rotational error/frame).
AB - In this contribution we present an approach for 2D-3D pose estimation of 3D free-form surface models. In our scenario we observe a free-form object in an image of a calibrated camera. Pose estimation means to estimate the relative position and orientation of the 3D object to the reference camera system. The object itself is modeled as a twoparametric 3D surface and extended by one-parametric contour parts of the object. A twist representation, which is equivalent to a Fourier representation allows for a low-pass approximation of the object model, which is advantageously applied to regularize the pose problem. The experiments show, that our developed algorithms are fast (200ms/frame) and accurate (1° rotational error/frame).
UR - http://www.scopus.com/inward/record.url?scp=35048832800&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-24670-1_32
DO - 10.1007/978-3-540-24670-1_32
M3 - Article
AN - SCOPUS:35048832800
VL - 3021
SP - 414
EP - 427
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SN - 0302-9743
ER -