@inproceedings{8bdf03dcc7fc42749d45b0ab05d82d41,
title = "Edge-Based Monocular Thermal Odometry in Low Illumination Environments",
abstract = "Achieving accurate motion estimation in low-illumination environments is challenging for traditional Visual Odometry (VO) that utilizes visible cameras. In contrast, long-wave infrared (LWIR) cameras can operate independently of illumination conditions. However, the direct applicability of traditional VO methods to thermal images is limited due to poor image quality. This paper proposes an edge-based monocular thermal Visual Odometry, which achieves motion estimation by matching edge feature points and incorporates loop detection to maintain global map consistency. Experimental results demonstrate that the system can achieve accurate and robust localization in low-illumination environments.",
keywords = "Edge features, Localization, Low illumination, Visual Odometry (VO)",
author = "Jun Hou and Tianyu Gao and Jinwen Hu and Zhao Xu and Mingwei Lyu",
note = "Publisher Copyright: {\textcopyright} Beijing HIWING Scientific and Technological Information Institute 2024.; 3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023 ; Conference date: 09-09-2023 Through 11-09-2023",
year = "2024",
doi = "10.1007/978-981-97-1103-1_18",
language = "英语",
isbn = "9789819711024",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "201--210",
editor = "Yi Qu and Mancang Gu and Yifeng Niu and Wenxing Fu",
booktitle = "Proceedings of 3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023 - Volume 7",
}