Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2019 International Conference on Computer Vision Workshop, ICCVW 2019 |
| Untertitel | Proceedings |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 569-578 |
| Seitenumfang | 10 |
| ISBN (elektronisch) | 978-1-7281-5023-9 |
| ISBN (Print) | 978-1-7281-5024-6 |
| Publikationsstatus | Veröffentlicht - Okt. 2019 |
| Veranstaltung | 2019 IEEE/CVF 17th International Conference on Computer Vision Workshop (ICCVW) - Seoul, Südkorea Dauer: 27 Okt. 2019 → 28 Okt. 2019 |
Publikationsreihe
| Name | IEEE International Conference on Computer Vision Workshops |
|---|---|
| ISSN (Print) | 2473-9936 |
| ISSN (elektronisch) | 2473-9944 |
Abstract
We propose a general, prior-free approach for the uncalibrated non-rigid structure-from-motion problem for modelling and analysis of non-rigid objects such as human faces. We recover the non-rigid affine structure and motion from 2D point correspondences by assuming that (1) the non-rigid shapes are generated by a linear combination of rigid 3D basis shapes, (2) that the non-rigid shapes are affine in nature, i.e., they can be modelled as deviations from the mean, rigid shape, (3) and that the basis shapes are statistically independent. In contrast to the majority of existing works, no statistical prior is assumed for the structure and motion apart from the assumption that underlying basis shapes are statistically independent. The independent 3D shape bases are recovered by independent subspace analysis (ISA). Likewise, in contrast to the most previous approaches, no calibration information is assumed for affine cameras; the reconstruction is solved up to a global affine ambiguity that makes our approach simple and efficient. In the experiments, we evaluated the method with several standard data sets including a real face expression data set of 7200 faces with 2D point correspondences and unknown 3D structure and motion for which we obtained promising results.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Angewandte Informatik
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
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2019 International Conference on Computer Vision Workshop, ICCVW 2019: Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. S. 569-578 9022195 (IEEE International Conference on Computer Vision Workshops).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Uncalibrated non-rigid factorisation by independent subspace analysis
AU - Brandt, Sami Sebastian
AU - Ackermann, Hanno
AU - Grasshof, Stella
PY - 2019/10
Y1 - 2019/10
N2 - We propose a general, prior-free approach for the uncalibrated non-rigid structure-from-motion problem for modelling and analysis of non-rigid objects such as human faces. We recover the non-rigid affine structure and motion from 2D point correspondences by assuming that (1) the non-rigid shapes are generated by a linear combination of rigid 3D basis shapes, (2) that the non-rigid shapes are affine in nature, i.e., they can be modelled as deviations from the mean, rigid shape, (3) and that the basis shapes are statistically independent. In contrast to the majority of existing works, no statistical prior is assumed for the structure and motion apart from the assumption that underlying basis shapes are statistically independent. The independent 3D shape bases are recovered by independent subspace analysis (ISA). Likewise, in contrast to the most previous approaches, no calibration information is assumed for affine cameras; the reconstruction is solved up to a global affine ambiguity that makes our approach simple and efficient. In the experiments, we evaluated the method with several standard data sets including a real face expression data set of 7200 faces with 2D point correspondences and unknown 3D structure and motion for which we obtained promising results.
AB - We propose a general, prior-free approach for the uncalibrated non-rigid structure-from-motion problem for modelling and analysis of non-rigid objects such as human faces. We recover the non-rigid affine structure and motion from 2D point correspondences by assuming that (1) the non-rigid shapes are generated by a linear combination of rigid 3D basis shapes, (2) that the non-rigid shapes are affine in nature, i.e., they can be modelled as deviations from the mean, rigid shape, (3) and that the basis shapes are statistically independent. In contrast to the majority of existing works, no statistical prior is assumed for the structure and motion apart from the assumption that underlying basis shapes are statistically independent. The independent 3D shape bases are recovered by independent subspace analysis (ISA). Likewise, in contrast to the most previous approaches, no calibration information is assumed for affine cameras; the reconstruction is solved up to a global affine ambiguity that makes our approach simple and efficient. In the experiments, we evaluated the method with several standard data sets including a real face expression data set of 7200 faces with 2D point correspondences and unknown 3D structure and motion for which we obtained promising results.
KW - Affine reconstruction
KW - Independent subspace analysis
KW - Non rigid structure from motion
UR - http://www.scopus.com/inward/record.url?scp=85082448778&partnerID=8YFLogxK
U2 - 10.48550/arXiv.1811.09132
DO - 10.48550/arXiv.1811.09132
M3 - Conference contribution
AN - SCOPUS:85082448778
SN - 978-1-7281-5024-6
T3 - IEEE International Conference on Computer Vision Workshops
SP - 569
EP - 578
BT - 2019 International Conference on Computer Vision Workshop, ICCVW 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/CVF 17th International Conference on Computer Vision Workshop (ICCVW)
Y2 - 27 October 2019 through 28 October 2019
ER -