Unscented Kalman filtering for articulated human tracking

Anders Boesen Lindbo Larsen, Søren Hauberg, Kim Steenstrup Pedersen

8 Citationer (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.
OriginalsprogEngelsk
TitelImage Analysis : 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May 2011. Proceedings
RedaktørerAnders Heyden, Fredrik Kahl
Antal sider10
ForlagSpringer
Publikationsdato2011
Sider228-237
ISBN (Trykt)978-3-642-21226-0
ISBN (Elektronisk)978-3-642-21227-7
DOI
StatusUdgivet - 2011
Begivenhed17th Scandinavian Conference on Image Analysis - Ystad, Sverige
Varighed: 23 maj 201127 maj 2011
Konferencens nummer: 17

Konference

Konference17th Scandinavian Conference on Image Analysis
Nummer17
Land/OmrådeSverige
ByYstad
Periode23/05/201127/05/2011
NavnLecture notes in computer science
Vol/bind6688
ISSN0302-9743

Fingeraftryk

Dyk ned i forskningsemnerne om 'Unscented Kalman filtering for articulated human tracking'. Sammen danner de et unikt fingeraftryk.

Citationsformater