Standard
Data-driven importance distributions for articulated tracking. / Hauberg, Søren; Pedersen, Kim Steenstrup.
Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011, St. Petersburg, Russia, July 25-27, 2011. Proceedings. ed. / Yuri Boykov; Fredrik Kahl; Victor Lempitsky; Frank R. Schmidt. Springer, 2011. p. 287-299 (Lecture notes in computer science, Vol. 6819).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Hauberg, S
& Pedersen, KS 2011,
Data-driven importance distributions for articulated tracking. in Y Boykov, F Kahl, V Lempitsky & FR Schmidt (eds),
Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011, St. Petersburg, Russia, July 25-27, 2011. Proceedings. Springer, Lecture notes in computer science, vol. 6819, pp. 287-299, 8th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, Sankt Petersborg, Russian Federation,
25/07/2011.
https://doi.org/10.1007/978-3-642-23094-3_21APA
Hauberg, S.
, & Pedersen, K. S. (2011).
Data-driven importance distributions for articulated tracking. In Y. Boykov, F. Kahl, V. Lempitsky, & F. R. Schmidt (Eds.),
Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011, St. Petersburg, Russia, July 25-27, 2011. Proceedings (pp. 287-299). Springer. Lecture notes in computer science Vol. 6819
https://doi.org/10.1007/978-3-642-23094-3_21Vancouver
Hauberg S
, Pedersen KS.
Data-driven importance distributions for articulated tracking. In Boykov Y, Kahl F, Lempitsky V, Schmidt FR, editors, Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011, St. Petersburg, Russia, July 25-27, 2011. Proceedings. Springer. 2011. p. 287-299. (Lecture notes in computer science, Vol. 6819).
https://doi.org/10.1007/978-3-642-23094-3_21Author
Hauberg, Søren ; Pedersen, Kim Steenstrup. / Data-driven importance distributions for articulated tracking. Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011, St. Petersburg, Russia, July 25-27, 2011. Proceedings. editor / Yuri Boykov ; Fredrik Kahl ; Victor Lempitsky ; Frank R. Schmidt. Springer, 2011. pp. 287-299 (Lecture notes in computer science, Vol. 6819).
Bibtex
@inproceedings{34c263e44e8948409111c1d668c64428,
title = "Data-driven importance distributions for articulated tracking",
abstract = "We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In order to keep the algorithms efficient, we represent human poses in terms of spatial joint positions. To ensure constant bone lengths, the joint positions are confined to a non-linear representation manifold embedded in a high-dimensional Euclidean space. We define the importance distributions in the embedding space and project them onto the representation manifold. The resulting importance distributions are used in a particle filter, where they improve both accuracy and efficiency of the tracker. In fact, they triple the effective number of samples compared to the most commonly used importance distribution at little extra computational cost.",
author = "S{\o}ren Hauberg and Pedersen, {Kim Steenstrup}",
year = "2011",
doi = "10.1007/978-3-642-23094-3_21",
language = "English",
isbn = "978-3-642-23093-6",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "287--299",
editor = "Yuri Boykov and Fredrik Kahl and Victor Lempitsky and Schmidt, {Frank R.}",
booktitle = "Energy Minimization Methods in Computer Vision and Pattern Recognition",
address = "Switzerland",
note = "null ; Conference date: 25-07-2011 Through 27-07-2011",
}
RIS
TY - GEN
T1 - Data-driven importance distributions for articulated tracking
AU - Hauberg, Søren
AU - Pedersen, Kim Steenstrup
N1 - Conference code: 8
PY - 2011
Y1 - 2011
N2 - We present two data-driven importance distributions for particle filterbased
articulated tracking; one based on background subtraction, another on depth
information. In order to keep the algorithms efficient, we represent human poses
in terms of spatial joint positions. To ensure constant bone lengths, the joint
positions are confined to a non-linear representation manifold embedded in a
high-dimensional Euclidean space. We define the importance distributions in the
embedding space and project them onto the representation manifold. The resulting
importance distributions are used in a particle filter, where they improve both
accuracy and efficiency of the tracker. In fact, they triple the effective number of
samples compared to the most commonly used importance distribution at little
extra computational cost.
AB - We present two data-driven importance distributions for particle filterbased
articulated tracking; one based on background subtraction, another on depth
information. In order to keep the algorithms efficient, we represent human poses
in terms of spatial joint positions. To ensure constant bone lengths, the joint
positions are confined to a non-linear representation manifold embedded in a
high-dimensional Euclidean space. We define the importance distributions in the
embedding space and project them onto the representation manifold. The resulting
importance distributions are used in a particle filter, where they improve both
accuracy and efficiency of the tracker. In fact, they triple the effective number of
samples compared to the most commonly used importance distribution at little
extra computational cost.
U2 - 10.1007/978-3-642-23094-3_21
DO - 10.1007/978-3-642-23094-3_21
M3 - Article in proceedings
SN - 978-3-642-23093-6
T3 - Lecture notes in computer science
SP - 287
EP - 299
BT - Energy Minimization Methods in Computer Vision and Pattern Recognition
A2 - Boykov, Yuri
A2 - Kahl, Fredrik
A2 - Lempitsky, Victor
A2 - Schmidt, Frank R.
PB - Springer
Y2 - 25 July 2011 through 27 July 2011
ER -
