A Step Towards Self-calibration in SLAM: Weakly Calibrated On-line Structure and Motion Estimation
Författare
Summary, in English
We propose a structure and motion estimation scheme based on a dynamic systems approach, where states and parameters in a perspective system are estimated. An online method for structure and motion estimation in densely sampled image sequences is presented. The proposed method is based on an extended Kalman filter and a novel parametrization. We derive a dynamic system describing the motion of the camera and the image formation. By a change of coordinates, we represent this system by normalized image coordinates and the inverse depths. Then we apply an extended Kalman filter for estimation of both structure and motion. Furthermore, we assume only weakly calibrated cameras, i.e. cameras with unknown and possibly varying focal length, unknown and constant principal point and known aspect ratio and skew. The performance of the proposed method is demonstrated in both simulated and real experiments. We also compare our method to the one proposed by Civera et al. and show that we get superior results.
Avdelning/ar
- Matematik LTH
- Mathematical Imaging Group
- ELLIIT: the Linköping-Lund initiative on IT and mobile communication
Publiceringsår
2010
Språk
Engelska
Sidor
59-64
Publikation/Tidskrift/Serie
Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on
Fulltext
Länkar
Dokumenttyp
Konferensbidrag
Förlag
IEEE - Institute of Electrical and Electronics Engineers Inc.
Ämne
- Computer Vision and Robotics (Autonomous Systems)
- Mathematics
Conference name
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2010
Conference date
2010-06-13 - 2010-06-18
Conference place
San Francisco, United States
Status
Published
Forskningsgrupp
- Mathematical Imaging Group
ISBN/ISSN/Övrigt
- ISSN: 2160-7508
- ISSN: 2160-7516
- ISBN: 978-1-4244-7029-7 (Print)