Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | Proceedings of the International Conference on Articulated Motion and Deformable Objects (AMDO) |
| Editors | F.J. Perales, R.B. Fisher |
| Place of Publication | Berlin |
| Publisher | Springer Verlag |
| Pages | 289-298 |
| Number of pages | 10 |
| ISBN (Print) | 978-3-540-70516-1 |
| DOIs | |
| State | Published - 27 Jun 2008 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer Verlag |
| Number | 274 |
| Volume | 5098 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
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Keywords
- EWI-12886
- EC Grant Agreement nr.: FP6/033812
- METIS-251011
- IR-64813
Cite this
}
Body-part templates for recovery of 2D human poses under occlusion. / Poppe, Ronald Walter; Poel, Mannes.
Proceedings of the International Conference on Articulated Motion and Deformable Objects (AMDO). ed. / F.J. Perales; R.B. Fisher. Berlin : Springer Verlag, 2008. p. 289-298 10.1007/978-3-540-70517-8_28 (Lecture Notes in Computer Science; Vol. 5098, No. 274).Research output: Scientific - peer-review › Conference contribution
TY - CHAP
T1 - Body-part templates for recovery of 2D human poses under occlusion
AU - Poppe,Ronald Walter
AU - Poel,Mannes
N1 - 10.1007/978-3-540-70517-8_28
PY - 2008/6/27
Y1 - 2008/6/27
N2 - Detection of humans and estimation of their 2D poses from a single image are challenging tasks. This is especially true when part of the observation is occluded. However, given a limited class of movements, poses can be recovered given the visible body-parts. To this end, we propose a novel template representation where the body is divided into five body-parts. Given a match, we not only estimate the joints in the body-part, but all joints in the body. Quantitative evaluation on a HumanEva walking sequence shows mean 2D errors of approximately 27.5 pixels. For simulated occlusion of the head and arms, similar results are obtained while occlusion of the legs increases this error by 6 pixels.
AB - Detection of humans and estimation of their 2D poses from a single image are challenging tasks. This is especially true when part of the observation is occluded. However, given a limited class of movements, poses can be recovered given the visible body-parts. To this end, we propose a novel template representation where the body is divided into five body-parts. Given a match, we not only estimate the joints in the body-part, but all joints in the body. Quantitative evaluation on a HumanEva walking sequence shows mean 2D errors of approximately 27.5 pixels. For simulated occlusion of the head and arms, similar results are obtained while occlusion of the legs increases this error by 6 pixels.
KW - EWI-12886
KW - EC Grant Agreement nr.: FP6/033812
KW - METIS-251011
KW - IR-64813
U2 - 10.1007/978-3-540-70517-8_28
DO - 10.1007/978-3-540-70517-8_28
M3 - Conference contribution
SN - 978-3-540-70516-1
T3 - Lecture Notes in Computer Science
SP - 289
EP - 298
BT - Proceedings of the International Conference on Articulated Motion and Deformable Objects (AMDO)
PB - Springer Verlag
ER -