Joint Forward-Backward Visual Odometry for Stereo Cameras

TL;DR

This paper introduces a joint forward-backward stereo visual odometry framework that enhances motion estimation accuracy by combining bidirectional estimates and assessing their reliability without ground truth.

Contribution

It proposes a novel joint forward-backward visual odometry method with reliability measures, improving accuracy over traditional methods using stereo cameras.

Findings

Enhanced pose estimation accuracy demonstrated on KITTI dataset

Reliability measures effectively evaluate odometry without ground truth

Real-time implementation on standard CPUs achieved

Abstract

Visual odometry is a widely used technique in the field of robotics and automation to keep a track on the location of a robot using visual cues alone. In this paper, we propose a joint forward backward visual odometry framework by combining both, the forward motion and backward motion estimated from stereo cameras. The basic framework of LIBVIOS2 is used here for pose estimation as it can run in real-time on standard CPUs. The complementary nature of errors in the forward and backward mode of visual odometry helps in providing a refined motion estimation upon combining these individual estimates. In addition, two reliability measures, that is, forward-backward relative pose error and forward-backward absolute pose error have been proposed for evaluating visual odometry frameworks on its own without the requirement of any ground truth data. The proposed scheme is evaluated on the KITTI visual odometry dataset. The experimental results demonstrate improved accuracy of the proposed scheme over the traditional odometry pipeline without much increase in the system overload.