Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Computer Vision - ECCV 2018 Workshops |
| Untertitel | Munich, Germany, September 8-14, 2018, Proceedings, Part IV |
| Herausgeber/-innen | Laura Leal-Taixé, Stefan Roth |
| Erscheinungsort | Cham |
| Seiten | 31-47 |
| Seitenumfang | 17 |
| Auflage | 1. |
| ISBN (elektronisch) | 978-3-030-11018-5 |
| Publikationsstatus | Veröffentlicht - 23 Jan. 2019 |
| Veranstaltung | 15th European Conference on Computer Vision, ECCV 2018 - Munich, Deutschland Dauer: 8 Sept. 2018 → 14 Sept. 2018 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 11132 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
This paper deals with motion capture of kinematic chains (e.g. human skeletons) from monocular image sequences taken by uncalibrated cameras. We present a method based on projecting an observation onto a kinematic chain space (KCS). An optimization of the nuclear norm is proposed that implicitly enforces structural properties of the kinematic chain. Unlike other approaches our method is not relying on training data or previously determined constraints such as particular body lengths. The proposed algorithm is able to reconstruct scenes with little or no camera motion and previously unseen motions. It is not only applicable to human skeletons but also to other kinematic chains for instance animals or industrial robots. We achieve state-of-the-art results on different benchmark databases and real world scenes.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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- BibTex
- RIS
Computer Vision - ECCV 2018 Workshops: Munich, Germany, September 8-14, 2018, Proceedings, Part IV. Hrsg. / Laura Leal-Taixé; Stefan Roth. 1. Aufl. Cham, 2019. S. 31-47 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 11132 LNCS).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - A kinematic chain space for monocular motion capture
AU - Wandt, Bastian
AU - Ackermann, Hanno
AU - Rosenhahn, Bodo
PY - 2019/1/23
Y1 - 2019/1/23
N2 - This paper deals with motion capture of kinematic chains (e.g. human skeletons) from monocular image sequences taken by uncalibrated cameras. We present a method based on projecting an observation onto a kinematic chain space (KCS). An optimization of the nuclear norm is proposed that implicitly enforces structural properties of the kinematic chain. Unlike other approaches our method is not relying on training data or previously determined constraints such as particular body lengths. The proposed algorithm is able to reconstruct scenes with little or no camera motion and previously unseen motions. It is not only applicable to human skeletons but also to other kinematic chains for instance animals or industrial robots. We achieve state-of-the-art results on different benchmark databases and real world scenes.
AB - This paper deals with motion capture of kinematic chains (e.g. human skeletons) from monocular image sequences taken by uncalibrated cameras. We present a method based on projecting an observation onto a kinematic chain space (KCS). An optimization of the nuclear norm is proposed that implicitly enforces structural properties of the kinematic chain. Unlike other approaches our method is not relying on training data or previously determined constraints such as particular body lengths. The proposed algorithm is able to reconstruct scenes with little or no camera motion and previously unseen motions. It is not only applicable to human skeletons but also to other kinematic chains for instance animals or industrial robots. We achieve state-of-the-art results on different benchmark databases and real world scenes.
UR - http://www.scopus.com/inward/record.url?scp=85061708581&partnerID=8YFLogxK
U2 - 10.48550/arXiv.1702.00186
DO - 10.48550/arXiv.1702.00186
M3 - Conference contribution
AN - SCOPUS:85061708581
SN - 978-3-030-11017-8
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 31
EP - 47
BT - Computer Vision - ECCV 2018 Workshops
A2 - Leal-Taixé, Laura
A2 - Roth, Stefan
CY - Cham
T2 - 15th European Conference on Computer Vision, ECCV 2018
Y2 - 8 September 2018 through 14 September 2018
ER -