Unscented Kalman filtering for articulated human tracking

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Standard

Unscented Kalman filtering for articulated human tracking. / Boesen Lindbo Larsen, Anders; Hauberg, Søren; Pedersen, Kim Steenstrup.

Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings. red. / Anders Heyden; Fredrik Kahl. Springer, 2011. s. 228-237 (Lecture notes in computer science, Bind 6688).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Harvard

Boesen Lindbo Larsen, A, Hauberg, S & Pedersen, KS 2011, Unscented Kalman filtering for articulated human tracking. i A Heyden & F Kahl (red), Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings. Springer, Lecture notes in computer science, bind 6688, s. 228-237, 17th Scandinavian Conference on Image Analysis, Ystad, Sverige, 23/05/2011. https://doi.org/10.1007/978-3-642-21227-7_22

APA

Boesen Lindbo Larsen, A., Hauberg, S., & Pedersen, K. S. (2011). Unscented Kalman filtering for articulated human tracking. I A. Heyden, & F. Kahl (red.), Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings (s. 228-237). Springer. Lecture notes in computer science Bind 6688 https://doi.org/10.1007/978-3-642-21227-7_22

Vancouver

Boesen Lindbo Larsen A, Hauberg S, Pedersen KS. Unscented Kalman filtering for articulated human tracking. I Heyden A, Kahl F, red., Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings. Springer. 2011. s. 228-237. (Lecture notes in computer science, Bind 6688). https://doi.org/10.1007/978-3-642-21227-7_22

Author

Boesen Lindbo Larsen, Anders ; Hauberg, Søren ; Pedersen, Kim Steenstrup. / Unscented Kalman filtering for articulated human tracking. Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings. red. / Anders Heyden ; Fredrik Kahl. Springer, 2011. s. 228-237 (Lecture notes in computer science, Bind 6688).

Bibtex

@inproceedings{ce6a5599f53a42118dc0cf84352ade7c,
title = "Unscented Kalman filtering for articulated human tracking",
abstract = "We present an articulated tracking system working with data from a single narrow baseline stereo camera. The use of stereo data allows for some depth disambiguation, a common issue in articulated tracking, which in turn yields likelihoods that are practically unimodal. While current state-of-the-art trackers utilize particle filters, our unimodal likelihood model allows us to use an unscented Kalman filter. This robust and efficient filter allows us to improve the quality of the tracker while using substantially fewer likelihood evaluations. The system is compared to one based on a particle filter with superior results. Tracking quality is measured by comparing with ground truth data from a marker-based motion capture system.",
author = "{Boesen Lindbo Larsen}, Anders and S{\o}ren Hauberg and Pedersen, {Kim Steenstrup}",
year = "2011",
doi = "10.1007/978-3-642-21227-7_22",
language = "English",
isbn = "978-3-642-21226-0",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "228--237",
editor = "Anders Heyden and Fredrik Kahl",
booktitle = "Image Analysis",
address = "Switzerland",
note = "null ; Conference date: 23-05-2011 Through 27-05-2011",

}

RIS

TY - GEN

T1 - Unscented Kalman filtering for articulated human tracking

AU - Boesen Lindbo Larsen, Anders

AU - Hauberg, Søren

AU - Pedersen, Kim Steenstrup

N1 - Conference code: 17

PY - 2011

Y1 - 2011

N2 - We present an articulated tracking system working with data from a single narrow baseline stereo camera. The use of stereo data allows for some depth disambiguation, a common issue in articulated tracking, which in turn yields likelihoods that are practically unimodal. While current state-of-the-art trackers utilize particle filters, our unimodal likelihood model allows us to use an unscented Kalman filter. This robust and efficient filter allows us to improve the quality of the tracker while using substantially fewer likelihood evaluations. The system is compared to one based on a particle filter with superior results. Tracking quality is measured by comparing with ground truth data from a marker-based motion capture system.

AB - We present an articulated tracking system working with data from a single narrow baseline stereo camera. The use of stereo data allows for some depth disambiguation, a common issue in articulated tracking, which in turn yields likelihoods that are practically unimodal. While current state-of-the-art trackers utilize particle filters, our unimodal likelihood model allows us to use an unscented Kalman filter. This robust and efficient filter allows us to improve the quality of the tracker while using substantially fewer likelihood evaluations. The system is compared to one based on a particle filter with superior results. Tracking quality is measured by comparing with ground truth data from a marker-based motion capture system.

U2 - 10.1007/978-3-642-21227-7_22

DO - 10.1007/978-3-642-21227-7_22

M3 - Article in proceedings

SN - 978-3-642-21226-0

T3 - Lecture notes in computer science

SP - 228

EP - 237

BT - Image Analysis

A2 - Heyden, Anders

A2 - Kahl, Fredrik

PB - Springer

Y2 - 23 May 2011 through 27 May 2011

ER -

ID: 170193916