Geometric-based Line Segment Tracking for HDR Stereo Sequences

TL;DR

This paper introduces a geometrical line segment matching method for HDR stereo sequences that is robust to illumination changes and suitable for real-time visual odometry, with improved speed but fewer matches.

Contribution

It presents a novel L1-minimization based geometric approach for line segment matching that outperforms appearance-based methods in challenging HDR environments.

Findings

Robust line segment matching in HDR conditions.

Significant speed-up over previous methods.

Effective in real-time visual odometry applications.

Abstract

In this work, we propose a purely geometrical approach for the robust matching of line segments for challenging stereo streams with severe illumination changes or High Dynamic Range (HDR) environments. To that purpose, we exploit the univocal nature of the matching problem, i.e. every observation must be corresponded with a single feature or not corresponded at all. We state the problem as a sparse, convex, L1-minimization of the matching vector regularized by the geometric constraints. This formulation allows for the robust tracking of line segments along sequences where traditional appearance-based matching techniques tend to fail due to dynamic changes in illumination conditions. Moreover, the proposed matching algorithm also results in a considerable speed-up of previous state of the art techniques making it suitable for real-time applications such as Visual Odometry (VO). This, of course, comes at expense of a slightly lower number of matches in comparison with appearance based methods, and also limits its application to continuous video sequences, as it is rather constrained to small pose increments between consecutive frames. We validate the claimed advantages by first evaluating the matching performance in challenging video sequences, and then testing the method in a benchmarked point and line based VO algorithm.