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  Real-time Hand Tracking Using a Sum of Anisotropic Gaussians Model

Sridhar, S., Rhodin, H., Seidel, H.-P., Oulasvirta, A., & Theobalt, C. (2014). Real-time Hand Tracking Using a Sum of Anisotropic Gaussians Model. In Proceedings of the 2nd International Conference on 3D Vision (pp. 319-326). Piscataway, NJ: IEEE explore. doi:10.1109/3DV.2014.37.

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Genre: Konferenzbeitrag
Latex : Real-time Hand Tracking Using a Sum of Anisotropic {Gaussians} Model

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arXiv:1602.03860.pdf (Preprint), 3MB
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File downloaded from arXiv at 2016-10-12 10:23 Accepted version of paper published at 3DV 2014
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 Urheber:
Sridhar, Srinath1, Autor           
Rhodin, Helge1, Autor           
Seidel, Hans-Peter1, Autor                 
Oulasvirta, Antti2, Autor           
Theobalt, Christian1, Autor                 
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              
2External Organizations, ou_persistent22              

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Schlagwörter: Computer Science, Computer Vision and Pattern Recognition, cs.CV
 Zusammenfassung: Real-time marker-less hand tracking is of increasing importance in
human-computer interaction. Robust and accurate tracking of arbitrary hand
motion is a challenging problem due to the many degrees of freedom, frequent
self-occlusions, fast motions, and uniform skin color. In this paper, we
propose a new approach that tracks the full skeleton motion of the hand from
multiple RGB cameras in real-time. The main contributions include a new
generative tracking method which employs an implicit hand shape representation
based on Sum of Anisotropic Gaussians (SAG), and a pose fitting energy that is
smooth and analytically differentiable making fast gradient based pose
optimization possible. This shape representation, together with a full
perspective projection model, enables more accurate hand modeling than a
related baseline method from literature. Our method achieves better accuracy
than previous methods and runs at 25 fps. We show these improvements both
qualitatively and quantitatively on publicly available datasets.

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Sprache(n): eng - English
 Datum: 2016-02-112015-02-092014
 Publikationsstatus: Erschienen
 Seiten: 8 p.
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: arXiv: 1602.03860
URI: http://arxiv.org/abs/1602.03860
BibTex Citekey: Sridhar2016arXiv1602.03860
DOI: 10.1109/3DV.2014.37
 Art des Abschluß: -

Veranstaltung

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Titel: 2nd International Conference on 3D Vision
Veranstaltungsort: Tokyo, Japan
Start-/Enddatum: 2014-12-08 - 2014-12-11

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Titel: Proceedings of the 2nd International Conference on 3D Vision
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Piscataway, NJ : IEEE explore
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 319 - 326 Identifikator: ISBN: 978-1-4799-7000-1