On Incremental Structure from Motion Using Lines

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TitreOn Incremental Structure from Motion Using Lines
Type de publicationJournal Article
Year of Publication2022
AuteursMateus A, Tahri O, A. Aguiar P, Lima PU, Miraldo P
JournalIEEE TRANSACTIONS ON ROBOTICS
Volume38
Pagination391-406
Date PublishedFEB
Type of ArticleArticle
ISSN1552-3098
Mots-clésCameras, Computer vision for automation, Estimation, incremental structure-from-motion (SfM), Kalman filters, Observers, Robots, Visual Servoing, visual-based navigation, visualization
Résumé

Humans tend to build environments with structure, which consists of mainly planar surfaces. From the intersection of planar surfaces arise straight lines. Lines have more degrees of freedom than points. Thus, line-based structure-from-motion (SfM) provides more information about the environment. In this article, we present solutions for SfM using lines, namely, incremental SfM. These approaches consist of designing state observers for a camera's dynamical visual system looking at a 3-D line. We start by presenting a model that uses spherical coordinates for representing the line's moment vector. We show that this parameterization has singularities, and, therefore, we introduce a more suitable model that considers the line's moment and shortest viewing ray. Concerning the observers, we present two different methodologies. The first uses a memory-less state-of-the-art framework for dynamic visual systems. Since the previous states of the robotic agent are accessible-while performing the 3-D mapping of the environment-the second approach aims at exploiting the use of memory to improve the estimation accuracy and convergence speed. The two models and the two observers are evaluated in simulation and real data, where mobile and manipulator robots are used.

DOI10.1109/TRO.2021.3085487