loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1
Multi-View AAM Fitting and Camera Calibration
Beijing, China
October 17-October 20
ISBN: 0-7695-2334-X
Seth Koterba, Carnegie Mellon University
Simon Baker, Carnegie Mellon University
Iain Matthews, Carnegie Mellon University
Changbo Hu, Carnegie Mellon University
Jing Xiao, Carnegie Mellon University
Jeffrey Cohn, Carnegie Mellon University
Takeo Kanade, Carnegie Mellon University
In this paper we study the relationship between multiview Active Appearance Model (AAM) fitting and camera calibration. In the first part of the paper we propose an algorithm to calibrate the relative orientation of a set of N > 1 cameras by fitting an AAM to sets of N images. In essence, we use the human face as a (non-rigid) calibration grid. Our algorithm calibrates a set of 2 ? 3 weak-perspective camera projection matrices, projections of the world coordinate system origin into the images, depths of the world coordinate system origin, and focal lengths. We demonstrate that the performance of this algorithm is comparable to a standard algorithm using a calibration grid. In the second part of the paper we show how calibrating the cameras improves the performance of multi-view AAM fitting.
Citation:
Seth Koterba, Simon Baker, Iain Matthews, Changbo Hu, Jing Xiao, Jeffrey Cohn, Takeo Kanade, "Multi-View AAM Fitting and Camera Calibration," iccv, vol. 1, pp.511-518, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005
Usage of this product signifies your acceptance of the Terms of Use.