Extension of IPM to Stereo Vision

As a consequence of the depth loss caused by the acquisition process, the use of a single two-dimensional image does not allow a three dimensional reconstruction of the world without the use of any a-priori knowledge. In addition, when the target is the reconstruction of the 3D space, the solution gets more and more complex due to the larger amount of computation required by well-known approaches, such as the processing of stereo images.

The traditional approach to stereo vision[7] can be divided into four steps:

  1. calibration of the vision system;
  2. localization of a feature in an image;
  3. identification and localization of the same feature in the other image;
  4. 3D reconstruction of the scene.
The problem of three dimensional reconstruction can be solved by the use of triangulations between points that correspond to the same feature (homologous points). Unfortunately, the determination of homologous points is a difficult task, however the introduction of some domain specific constraints (such as the assumption of a flat road in front of the cameras) can simplify it. In particular, when a complete 3D reconstruction is not required and the verification of the match with a given surface model suffices, the application of IPM to stereo images plays a strategic role.

More precisely, since IPM can be used to recover the texture of a specific surface (the road plane in the previous discussion), when it is applied to both stereo images (with different parameters reflecting the different acquisition setup of the two cameras) it provides two instances of the given surface, namely two partially overlapping patches. These two patches, thanks to the knowledge of the vision system setup, can be brought to correspondence, so that the homologous points share the same coordinates in the two remapped images.