Towards Fast and Automatic Map Initialization for Monocular SLAM Systems

Blake Troutman, Mihran Tuceryan

2021

Abstract

Simultaneous localization and mapping (SLAM) is a widely adopted approach for estimating the pose of a sensor with 6 degrees of freedom. SLAM works by using sensor measurements to initialize and build a virtual map of the environment, while simultaneously matching succeeding sensor measurements to entries in the map to perform robust pose estimation of the sensor on each measurement cycle. Markerless, single-camera systems that utilize SLAM usually involve initializing the map by applying one of a few structure-from-motion approaches to two frames taken by the system at different points in time. However, knowing when the feature matches between two frames will yield enough disparity, parallax, and/or structure for a good initialization to take place remains an open problem. To make this determination, we train a number of logistic regression models on summarized correspondence data for 927 stereo image pairs. Our results show that these models classify with significantly higher precision than the current state-of-the-art approach in addition to remaining computationally inexpensive.

Paper Citation

in Harvard Style

Troutman B. and Tuceryan M. (2021). Towards Fast and Automatic Map Initialization for Monocular SLAM Systems. In Proceedings of the 2nd International Conference on Robotics, Computer Vision and Intelligent Systems - Volume 1: ROBOVIS, ISBN 978-989-758-537-1, pages 22-30. DOI: 10.5220/0010640600003061

in Bibtex Style

@conference{robovis21,
author={Blake Troutman and Mihran Tuceryan},
title={Towards Fast and Automatic Map Initialization for Monocular SLAM Systems},
booktitle={Proceedings of the 2nd International Conference on Robotics, Computer Vision and Intelligent Systems - Volume 1: ROBOVIS,},
year={2021},
pages={22-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010640600003061},
isbn={978-989-758-537-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Robotics, Computer Vision and Intelligent Systems - Volume 1: ROBOVIS,
TI - Towards Fast and Automatic Map Initialization for Monocular SLAM Systems
SN - 978-989-758-537-1
AU - Troutman B.
AU - Tuceryan M.
PY - 2021
SP - 22
EP - 30
DO - 10.5220/0010640600003061