Here is an example of what can be done with two rectified images. With two uncalibrated images, you can only obtain a projective
reconstruction of the scene, so you have to self-calibrate the camera. However, the case of rectified images, corresponding to
a pure translation camera movement, is a critical case of self-calibration. Even with usual hypotheses on the camera
internal parameters, the focal length remains undeterminable. So we have to tune the focal by hand.
The Plane-Based Self-Calibration problem is a non linear problem which consists of
the estimation of the internal parameters of the camera along with the Euclidean
structure of the plane. What we have at our disposal are several views of a
plane and the inter-view homographies. We have shown that there is an
interdependence in the parameterization introduced by Triggs in 1998.
Moreover, we have used Interval Analysis-Based Global Optimization
to solve the problem and find guaranteed solutions to this problem.
From the resulting parameters, we can compute an Euclidean rectification of
the key view and propagate this rectification to the other views in order to
make a mosaic. The following illustration shows a rectified mosaic and 4 views
among the 5 used to make the mosaic.
[ Stereovision: Generation of stereo images with ground truth ]
Synthetic images with ground truth.
Exact ground truth is only available for synhetic images. We proposed new photorealistic stereo images with the associated ground truth.
Two examples:
Blender script for the generation of ground truth from a 3d model: Download section.
References :
Benoît Bocquillon, Sylvie Chambon, Alain Crouzil. Segmentation semi-automatique en plans pour la génération de cartes denses de disparités. ORASIS05.
Ground truth from piecewise planar scenes.
We considered piecewise planar scenes and we proposed a method and a tool to get semiautomatically a plane-based segmentation of the images and to generate
accurate disparity maps. The semiautomatic segmentation helps to handle better the occlusions. The disparities are obtained from inter-images homographies.
Here is a new stereo image pair with the associated ground truth:
Tool for the generation of ground truth from stereo images of a piecewise planar scene: Download section.
References :
Benoît Bocquillon, Sylvie Chambon, Alain Crouzil. Segmentation semi-automatique en plans pour la génération de cartes denses de disparités. ORASIS05.
[ 3D reconstruction from two rectified images ]
