A self-supervised near-to-far approach for terrain-adaptive off-road autonomous driving

Loading...
Thumbnail Image

Authors

Mayuku, Orighomisan
Surgenor, Brian W.
Marshall, Joshua A.

Date

2021-07-05

Type

preprint

Language

en

Keyword

robotics , visualization , image colour analysis , convolutional neural networks , autonomous vehicles

Research Projects

Organizational Units

Journal Issue

Alternative Title

Abstract

For use in off-road autonomous driving applications, we propose and study the use of multi-resolution local binary pattern texture descriptors to improve overall semantic segmentation performance and reduce class imbalance effects in off-road visual datasets. Our experiments, using a challenging publicly available off-road dataset as well as our own off-road dataset, show that texture features provide added flexibility towards reducing class imbalance effects, and that fusing color and texture features can improve segmentation performance. Finally, we demonstrate domain adaptation limitations in nominally similar off-road environments by cross-comparing the segmentation performance of convolutional neural networks trained on both datasets.

Description

Citation

Publisher

IEEE

License

Journal

Volume

Issue

PubMed ID

External DOI

ISSN

EISSN

Collections