Superimposing Thermal-Infrared Data on 3D Structure Reconstructed by RGB Visual Odometry
| العنوان: | Superimposing Thermal-Infrared Data on 3D Structure Reconstructed by RGB Visual Odometry |
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| المؤلفون: | Hideo Saito, Vincent Nozick, Hideaki Sato, Shohei Mori, Shoji Yachida, Trong Phuc Truong, Masahiro Yamaguchi |
| المساهمون: | Faculty of Science and Technology, Keio University, Faculty of Science and Technology (Keio University) |
| المصدر: | IEICE Transactions on Information and Systems IEICE Transactions on Information and Systems, Institute of Electronics, Information and Communication Engineers, 2018, E101.D (5), pp.1296-1307. ⟨10.1587/transinf.2017MVP0023⟩ |
| بيانات النشر: | Institute of Electronics, Information and Communications Engineers (IEICE), 2018. |
| سنة النشر: | 2018 |
| مصطلحات موضوعية: | 0209 industrial biotechnology, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Point cloud, 02 engineering and technology, 020901 industrial engineering & automation, Odometry, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Point (geometry), Computer vision, Electrical and Electronic Engineering, Visual odometry, ComputingMethodologies_COMPUTERGRAPHICS, Delaunay triangulation, business.industry, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Hardware and Architecture, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], RGB color model, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, Scale (map), business, Software |
| الوصف: | International audience; In this paper, we propose a method to generate a three-dimensional (3D) thermal map and RGB + thermal (RGB-T) images of a scene from thermal-infrared and RGB images. The scene images are acquired by moving both a RGB camera and an thermal-infrared camera mounted on a stereo rig. Before capturing the scene with those cameras, we estimate their respective intrinsic parameters and their relative pose. Then, we reconstruct the 3D structures of the scene by using Direct Sparse Odometry (DSO) using the RGB images. In order to superimpose thermal information onto each point generated from DSO, we propose a method for estimating the scale of the point cloud corresponding to the ex-trinsic parameters between both cameras by matching depth images recovered from the RGB camera and the thermal-infrared camera based on mutual information. We also generate RGB-T images using the 3D structure of the scene and Delaunay triangulation. We do not rely on depth cameras and, therefore, our technique is not limited to scenes within the measurement range of the depth cameras. To demonstrate this technique, we generate 3D thermal maps and RGB-T images for both indoor and outdoor scenes. |
| تدمد: | 1745-1361 0916-8532 |
| DOI: | 10.1587/transinf.2017mvp0023 |
| DOI: | 10.1587/transinf.2017MVP0023⟩ |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f606ea91c716ec4c06569f87c20f94a6 https://doi.org/10.1587/transinf.2017mvp0023 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....f606ea91c716ec4c06569f87c20f94a6 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 17451361 09168532 |
|---|---|
| DOI: | 10.1587/transinf.2017mvp0023 |