Robotics: Science and Systems XI
Probabilistic Semi-Dense Mapping from Highly Accurate Feature-Based Monocular SLAM
Raul Mur-Artal, Juan TardosAbstract:
In the last years several direct (i.e. featureless) monocular SLAM approaches have appeared showing impressive semi-dense or dense scene reconstructions. These works have questioned the need of features, in which consolidated SLAM techniques of the last decade were based. In this paper we present a novel feature-based monocular SLAM system that is more robust, gives more accurate camera poses, and obtains comparable or better semi-dense reconstructions than the current state of the art. Our semi-dense mapping operates over keyframes, optimized by local bundle adjustment, allowing to obtain accurate triangulations from wide baselines. Our novel method to search correspondences, the measurement fusion and the inter-keyframe depth consistency tests allow to obtain clean reconstructions with very few outliers. Against the current trend in direct SLAM, our experiments show that by decoupling the semi-dense reconstruction from the trajectory computation, the results obtained are better. This opens the discussion on the benefits of features even if a semi-dense reconstruction is desired.
Bibtex:
@INPROCEEDINGS{Mur-Artal-RSS-15, AUTHOR = {Raul Mur-Artal AND Juan Tardos}, TITLE = {Probabilistic Semi-Dense Mapping from Highly Accurate Feature-Based Monocular SLAM}, BOOKTITLE = {Proceedings of Robotics: Science and Systems}, YEAR = {2015}, ADDRESS = {Rome, Italy}, MONTH = {July}, DOI = {10.15607/RSS.2015.XI.041} }