Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Advances in Visual Computing |
| Untertitel | 9th International Symposium, ISVC 2013, Proceedings |
| Seiten | 592-602 |
| Seitenumfang | 11 |
| Auflage | PART 2 |
| Publikationsstatus | Veröffentlicht - 2013 |
| Veranstaltung | 9th International Symposium on Advances in Visual Computing, ISVC 2013 - Rethymnon, Crete, Griechenland Dauer: 29 Juli 2013 → 31 Juli 2013 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Nummer | PART 2 |
| Band | 8034 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
Hand pose estimation is an important task in areas such as human computer interaction (HCI), sign language recognition and robotics. Due to the high variability in hand appearance and many degrees of freedom (DoFs) of the hand, hand pose estimation and tracking is very challenging, and different sources of data and methods are used to solve this problem. In the paper, we propose a method for model-based full DoF hand pose estimation from a single RGB-D image. The main advantage of the proposed method is that no prior manual initialization is required and only very general assumptions about the hand pose are made. Therefore, this method can be used for hand pose estimation from a single RGB-D image, as an initialization step for subsequent tracking, or for tracking recovery.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
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Advances in Visual Computing: 9th International Symposium, ISVC 2013, Proceedings. PART 2. Aufl. 2013. S. 592-602 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 8034 LNCS, Nr. PART 2).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Hand pose estimation from a single RGB-D image
AU - Kuznetsova, Alina
AU - Rosenhahn, Bodo
N1 - Funding information: This work has been partially funded by the ERC within the starting grant Dynamic MinVIP.
PY - 2013
Y1 - 2013
N2 - Hand pose estimation is an important task in areas such as human computer interaction (HCI), sign language recognition and robotics. Due to the high variability in hand appearance and many degrees of freedom (DoFs) of the hand, hand pose estimation and tracking is very challenging, and different sources of data and methods are used to solve this problem. In the paper, we propose a method for model-based full DoF hand pose estimation from a single RGB-D image. The main advantage of the proposed method is that no prior manual initialization is required and only very general assumptions about the hand pose are made. Therefore, this method can be used for hand pose estimation from a single RGB-D image, as an initialization step for subsequent tracking, or for tracking recovery.
AB - Hand pose estimation is an important task in areas such as human computer interaction (HCI), sign language recognition and robotics. Due to the high variability in hand appearance and many degrees of freedom (DoFs) of the hand, hand pose estimation and tracking is very challenging, and different sources of data and methods are used to solve this problem. In the paper, we propose a method for model-based full DoF hand pose estimation from a single RGB-D image. The main advantage of the proposed method is that no prior manual initialization is required and only very general assumptions about the hand pose are made. Therefore, this method can be used for hand pose estimation from a single RGB-D image, as an initialization step for subsequent tracking, or for tracking recovery.
UR - http://www.scopus.com/inward/record.url?scp=84888237482&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-41939-3_58
DO - 10.1007/978-3-642-41939-3_58
M3 - Conference contribution
AN - SCOPUS:84888237482
SN - 9783642419386
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 592
EP - 602
BT - Advances in Visual Computing
T2 - 9th International Symposium on Advances in Visual Computing, ISVC 2013
Y2 - 29 July 2013 through 31 July 2013
ER -