Depth Estimation Analysis of Orthogonally Divergent Fisheye Cameras with
  Distortion Removal
Matvei Panteleev Houari Bettahar
Stereo vision systems have become popular in computer vision applications,
such as 3D reconstruction, object tracking, and autonomous navigation. However,
traditional stereo vision systems that use rectilinear lenses may not be
suitable for certain scenarios due to their limited field of view. This has led
to the popularity of vision systems based on one or multiple fisheye cameras in
different orientations, which can provide a field of view of 180x180 degrees or
more. However, fisheye cameras introduce significant distortion at the edges
that affects the accuracy of stereo matching and depth estimation. To overcome
these limitations, this paper proposes a method for distortion-removal and
depth estimation analysis for stereovision system using orthogonally divergent
fisheye cameras (ODFC). The proposed method uses two virtual pinhole cameras
(VPC), each VPC captures a small portion of the original view and presents it
without any lens distortions, emulating the behavior of a pinhole camera. By
carefully selecting the captured regions, it is possible to create a stereo
pair using two VPCs. The performance of the proposed method is evaluated in
both simulation using virtual environment and experiments using real cameras
and their results compared to stereo cameras with parallel optical axes. The
results demonstrate the effectiveness of the proposed method in terms of
distortion removal and depth estimation accuracy.