The KITTI Vision Benchmark Suite

Elbrus is a Stereo SLAM technology.

It assumes a calibrated stereo rig
(intrinsics and extrinsic of the cameras are
known, including the baseline distance) and known
lens distortion parameters
(Brown's distortion model).

Elbrus contains two
major components.
The 2D component is based on
multi-pyramid KLT feature tracking with local
average luminance compensation.
The 3D component
uses keyframes selected using 2D track average
motion and rate of disappearance criteria. The 2D
tracking of each feature is guided by the
prediction of the track's position provided by
the results of 3D tracking.

3D tracking is done via the exponential mapping
formalism for
recovering the six absolute orientation
parameters of the camera rig using standard
elements of triangulation, resectioning and
sparse bundle adjustment (SBA).

SBA runs on a
separate thread in parallel with the rest of the
Elbrus VO calculations.

For NVIDIA Xavier Elbrus can track on 144fps.

-lr_tracker=lk_horizontal -use_gpu=true

@unpublished{ELBRUS2018,
title={Realtime Stereo Visual Odometry},
author={
Alexander Korovko and
Dmitry Robustov and
Dmitry Slepichev and
Eugene Vendrovsky and
Stanislav Volodarskiy
},
}