Full-Time Monocular Road Detection Using Zero-Distribution Prior of Angle of Polarization
Abstract
This paper presents a road detection technique based on long-wave infrared (LWIR) polarization imaging for autonomous navigation regardless of illumination conditions, day and night. Division of Focal Plane (DoFP) imaging technology enables acquisition of infrared polarization images in real time using a monocular camera. Zero-distribution prior embodies the zero-distribution of Angle of Polarization (AoP) of a road scene image, which provides a significant contrast between the road and the background. This paper combines zero-distribution of AoP, the difference of Degree of linear Polarization (DoP), and the edge information to segment the road region in the scene. We developed a LWIR DoFP Dataset of Road Scene (LDDRS) consisting of 2,113 annotated images. Experiment results on the LDDRS dataset demonstrate the merits of the proposed road detection method based on the zero-distribution prior. The LDDRS dataset is available at https://github.com/polwork/LDDRS
Cite
Text
Li et al. "Full-Time Monocular Road Detection Using Zero-Distribution Prior of Angle of Polarization." Proceedings of the European Conference on Computer Vision (ECCV), 2020. doi:10.1007/978-3-030-58595-2_28Markdown
[Li et al. "Full-Time Monocular Road Detection Using Zero-Distribution Prior of Angle of Polarization." Proceedings of the European Conference on Computer Vision (ECCV), 2020.](https://mlanthology.org/eccv/2020/li2020eccv-fulltime/) doi:10.1007/978-3-030-58595-2_28BibTeX
@inproceedings{li2020eccv-fulltime,
title = {{Full-Time Monocular Road Detection Using Zero-Distribution Prior of Angle of Polarization}},
author = {Li, Ning and Zhao, Yongqiang and Pan, Quan and Kong, Seong G. and Chan, Jonathan Cheung-Wai},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2020},
doi = {10.1007/978-3-030-58595-2_28},
url = {https://mlanthology.org/eccv/2020/li2020eccv-fulltime/}
}