An important problem in active 3-D vision is updating the camera calibration matrix as the focus, aperture, zoom or vergence angle of the cameras changes dynamically. Techniques are presented to compute the projection matrix from five-and-a-half points in a scene without matrix inversion, and to correct the projective transformation matrix by tracking reference points. The authors' experiments show that a change of focus can be corrected by an affine transform obtained by tracking three points. For a change in camera vergence, a projective correction, based on tracking four image points, is slightly more precise than an affine correction matrix. It is shown how stereo reconstruction makes it possible to 'hop' a reference frame from one object to another. Any set of four non-coplanar points in the scene may define such a reference frame. It is shown how to keep the reference frame locked onto a set of four points as a stereo head is translated or rotated. These techniques make it possible to reconstruct the shape of an object in in its intrinsic coordinates without having to match new observations to a partially reconstructed description.<<ETX>>
[1]
Thomas Skordas,et al.
Calibrating a mobile camera
,
1990,
Image Vis. Comput..
[2]
Roger Y. Tsai,et al.
A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses
,
1987,
IEEE J. Robotics Autom..
[3]
J J Koenderink,et al.
Affine structure from motion.
,
1991,
Journal of the Optical Society of America. A, Optics and image science.
[4]
Gunnar Sparr.
Depth Computations from Polyhedral Images
,
1992,
ECCV.
[5]
Cordelia Schmid,et al.
Auto-calibration by direct observation of objects
,
1993,
Image Vis. Comput..
[6]
James L. Crowley,et al.
Towards Continuously Operating Integrated Vision Systems for Robotics Applications
,
1992
.
[7]
Luce Morin,et al.
Relative Positioning with Poorly Calibrated Cameras
,
1990
.