Elaborate Monocular Point and Line SLAM With Robust Initialization

Sang Jun Lee, Sung Soo Hwang; The IEEE International Conference on Computer Vision (ICCV), 2019, pp. 1121-1129

Abstract


This paper presents a monocular indirect SLAM system which performs robust initialization and accurate localization. For initialization, we utilize a matrix factorization-based method. Matrix factorization-based methods require that extracted feature points must be tracked in all used frames. Since consistent tracking is difficult in challenging environments, a geometric interpolation that utilizes epipolar geometry is proposed. For localization, 3D lines are utilized. We propose the use of Plu cker line coordinates to represent geometric information of lines. We also propose orthonormal representation of Plu cker line coordinates and Jacobians of lines for better optimization. Experimental results show that the proposed initialization generates consistent and robust map in linear time with fast convergence even in challenging scenes. And localization using proposed line representations is faster, more accurate and memory efficient than other state-of-the-art methods.

Related Material


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[bibtex]
@InProceedings{Lee_2019_ICCV,
author = {Lee, Sang Jun and Hwang, Sung Soo},
title = {Elaborate Monocular Point and Line SLAM With Robust Initialization},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}