This paper analyses the influence of the stereo camera parameters on an existing obstacle detection technique. A theoretical model is derived and evaluated for the concepts of resolution and stability. Resolution is the minimum height that an obstacle must have in order to be detected. Stability is defined as the sensitivity of detection to errors in the camera parameters. It can be seen that detection is very sensitive to some of the parameters and that there is no clear tradeoff between resolution and stability. We derive a stereo head configuration to give stable results and show how the parameters should be adapted in the context of an active vision system. Experiments confirm the theoretical results.>

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.>

The authors present a method for using objects in a scene to define the reference frame for 3-D reconstruction. They first present a simple technique to calibrate an orthographic projection from four non-coplanar reference points. It is then shown that the observation of two additional known scene points can provide the complete perspective projection. When used with a known object, this technique permits a calibration of the full projective transformation matrix. For an arbitrary non-coplanar set of four points, this calibration provides an affine basis for the reconstruction of local scene structure. When the four points define three orthogonal vectors, the basis is orthogonal, with a metric defined by the lengths of the three vectors. This technique is demonstrated for the case of a cube. Results are presented in which five and a half points on the cube are sufficient to compute the projective transformation for an orthogonal basis by direct observation without matrix inversion. Experiments are outlined for reducing the imprecision due to pixel quantization and noise.>

This paper describes a layered control system for a binocular stereo head. It begins by a discussion of the principles of layered control. It then describes the mechanical configuration for a binocular camera head with six degrees of freedom. A device level controller is presented which permits an active vision system to command the position of a binocular gaze point in the scene. The final section describes the design of perceptual actions which exploit this device level controller.