Multilinear pose and body shape estimation of dressed subjects from image sets

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Nils Hasler
  • Hanno Ackermann
  • Bodo Rosenhahn
  • Thorsten Thormählen
  • Hans Peter Seidel

Externe Organisationen

  • Max-Planck-Institut für Informatik
  • Universität des Saarlandes
  • Weta Digital Ltd.
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des Sammelwerks2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Seiten1823-1830
Seitenumfang8
PublikationsstatusVeröffentlicht - 2010
Veranstaltung2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, CA, USA / Vereinigte Staaten
Dauer: 13 Juni 201018 Juni 2010

Publikationsreihe

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Abstract

In this paper we propose a multilinear model of human pose and body shape which is estimated from a database of registered 3D body scans in different poses. The model is generated by factorizing the measurements into pose and shape dependent components. By combining it with an ICP based registration method, we are able to estimate pose and body shape of dressed subjects from single images. If several images of the subject are available, shape and poses can be optimized simultaneously for all input images. Additionally, while estimating pose and shape, we use the model as a virtual calibration pattern and also recover the parameters of the perspective camera model the images were created with.

ASJC Scopus Sachgebiete

Zitieren

Multilinear pose and body shape estimation of dressed subjects from image sets. / Hasler, Nils; Ackermann, Hanno; Rosenhahn, Bodo et al.
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. S. 1823-1830 5539853 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Hasler, N, Ackermann, H, Rosenhahn, B, Thormählen, T & Seidel, HP 2010, Multilinear pose and body shape estimation of dressed subjects from image sets. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010., 5539853, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, S. 1823-1830, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, USA / Vereinigte Staaten, 13 Juni 2010. https://doi.org/10.1109/CVPR.2010.5539853
Hasler, N., Ackermann, H., Rosenhahn, B., Thormählen, T., & Seidel, H. P. (2010). Multilinear pose and body shape estimation of dressed subjects from image sets. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 (S. 1823-1830). Artikel 5539853 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). https://doi.org/10.1109/CVPR.2010.5539853
Hasler N, Ackermann H, Rosenhahn B, Thormählen T, Seidel HP. Multilinear pose and body shape estimation of dressed subjects from image sets. in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. S. 1823-1830. 5539853. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). doi: 10.1109/CVPR.2010.5539853
Hasler, Nils ; Ackermann, Hanno ; Rosenhahn, Bodo et al. / Multilinear pose and body shape estimation of dressed subjects from image sets. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010. 2010. S. 1823-1830 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).
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abstract = "In this paper we propose a multilinear model of human pose and body shape which is estimated from a database of registered 3D body scans in different poses. The model is generated by factorizing the measurements into pose and shape dependent components. By combining it with an ICP based registration method, we are able to estimate pose and body shape of dressed subjects from single images. If several images of the subject are available, shape and poses can be optimized simultaneously for all input images. Additionally, while estimating pose and shape, we use the model as a virtual calibration pattern and also recover the parameters of the perspective camera model the images were created with.",
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