Multi-View AAM Fitting and Camera Calibration - Robotics Institute Carnegie Mellon University

Multi-View AAM Fitting and Camera Calibration

Seth C. Koterba, Simon Baker, Iain Matthews, Changbo Hu, Jing Xiao, Jeffrey Cohn, and Takeo Kanade
Conference Paper, Proceedings of (ICCV) International Conference on Computer Vision, Vol. 1, pp. 511 - 518, October, 2005

Abstract

In this paper we study the relationship between multi-view 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 x 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.

BibTeX

@conference{Koterba-2005-9318,
author = {Seth C. Koterba and Simon Baker and Iain Matthews and Changbo Hu and Jing Xiao and Jeffrey Cohn and Takeo Kanade},
title = {Multi-View AAM Fitting and Camera Calibration},
booktitle = {Proceedings of (ICCV) International Conference on Computer Vision},
year = {2005},
month = {October},
volume = {1},
pages = {511 - 518},
}