Unscented Kalman filtering for articulated human tracking

Anders Boesen Lindbo Larsen; Søren Hauberg; Kim Steenstrup Pedersen

doi:10.1007/978-3-642-21227-7_22

Unscented Kalman filtering for articulated human tracking

Anders Boesen Lindbo Larsen, Søren Hauberg, Kim Steenstrup Pedersen

Department of Computer Science

8 Citations (Scopus)

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.

Original language	English
Title of host publication	Image Analysis : 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings
Editors	Anders Heyden, Fredrik Kahl
Number of pages	10
Publisher	Springer
Publication date	2011
Pages	228-237
ISBN (Print)	978-3-642-21226-0
ISBN (Electronic)	978-3-642-21227-7
DOIs	https://doi.org/10.1007/978-3-642-21227-7_22
Publication status	Published - 2011
Event	17th Scandinavian Conference on Image Analysis - Ystad, Sweden Duration: 23 May 2011 → 27 May 2011 Conference number: 17

Conference

Conference	17th Scandinavian Conference on Image Analysis
Number	17
Country/Territory	Sweden
City	Ystad
Period	23/05/2011 → 27/05/2011

Series	Lecture notes in computer science
Volume	6688
ISSN	0302-9743

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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. ed. / Anders Heyden; Fredrik Kahl. Springer, 2011. p. 228-237 (Lecture notes in computer science, Vol. 6688).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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

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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.

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Unscented Kalman filtering for articulated human tracking

Abstract

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