STheReO: Stereo Thermal Dataset for Research in Odometry and Mapping

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(2022)

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摘要
This paper introduces a stereo thermal camera dataset (STheReO) with multiple navigation sensors to encourage thermal SLAM researches. A thermal camera measures infrared rays beyond the visible spectrum therefore it could provide a simple yet robust solution to visually degraded environments where existing visual sensor-based SLAM would fail. Existing thermal camera datasets mostly focused on monocular configuration using the thermal camera with RGB cameras in a visually challenging environment. A few stereo thermal rig were examined but in computer vision perspective without supporting sequential images for state estimation algorithms. To encourage the academia for the evolving stereo thermal SLAM, we obtain nine sequences in total across three spatial locations and three different times per location (e.g., morning, day, and night) to capture the variety of thermal characteristics. By using the STheReO dataset, we hope diverse types of researches will be made, including but not limited to odometry, mapping, and SLAM (e.g., thermal-LiDAR mapping or long-term thermal localization). Our datasets are available at https://sites.google.com/view/rpmsthereo/.
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关键词
computer vision,infrared rays,mapping research,monocular configuration,multiple navigation sensors,odometry research,sequential images,state estimation algorithms,stereo thermal camera dataset,stereo thermal dataset,stereo thermal rig,stereo thermal SLAM,STheReO dataset,thermal camera,thermal SLAM
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