Visualization of Temperature Change Using RGB-D Camera and Thermal Camera

Nakagawa, Wataru; Matsumoto, Kazuki; Sorbier, Francois de; Sugimoto, Maki; Saitō, Hideo; Senda, Shuji; Shibata, Takashi; Iketani, Akihiko

doi:10.1007/978-3-319-16178-5_27

Cited by 12 publications

(4 citation statements)

References 11 publications

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“…In (21), the authors report root mean squared errors of thermal/depth extrinsics of 0,42 pixels. Moreover, in (30), the authors report a mean calibration error of up to 4 px. Thereupon, considering the reprojection errors reported and the fact that two kinds of extrinsic were computed (RGB/depth and thermal/depth), this work has achieved good results.…”

Section: Discussionmentioning

confidence: 97%

Software Tool for the Extrinsic Calibration of Infrared and RGBD Cameras Applied to Thermographic Inspection

Taimal

Bacca-Cortes

Girón

2022

Ing.

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Context: Thermographic inspections are currently used to assess energy efficiency in electrical equipment and civil structures or to detect failures in cooling systems and electrical or electronic devices. However, thermal images lack texture details, which does not allow for a precise identification of the geometry of the scene or the objects in it. Method: In this work, the development of the software tool called DepTherm is described. This tool allows performing intrinsic and extrinsic calibration between infrared and RGBD cameras in order to fuse thermal, RGB, and RGBD images, as well as to record thermal and depth data. Additional features include user management, a visualization GUI for all three types of images, database storage, and report generation. Results: In addition to the integration tests performed to validate the functionality of DepTherm, two quantitative tests were conducted in order to evaluate its accuracy. A maximum re-projection error of 1,47±0,64 pixels was found, and the maximum mean error in registering an 11 cm side cube was 4,15 mm. Conclusions: The features of the DepTherm software tool are focused on facilitating thermographic inspections by capturing 3D scene models with thermal data.

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Section: Discussionmentioning

confidence: 97%

Software Tool for the Extrinsic Calibration of Infrared and RGBD Cameras Applied to Thermographic Inspection

Taimal

Bacca-Cortes

Girón

2022

Ing.

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“…We demonstrate the use of our AR system by visualizing chansing temperatures of electrical equipment within a scene in real-time. This system can visualize more widespread thermal distribution than our previous work (Nakagawa et al, 2014).…”

Section: Ar Visualization Of Temperature Changes Distributionmentioning

confidence: 93%

AR Visualization of Thermal 3D Model by Hand-held Cameras

Matsumoto

Nakagawa

Saitō³

et al. 2015

Proceedings of the 10th International Conference on Computer Vision Theory and Applications

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In this paper, we propose a system for AR visualization of thermal distribution on the environment. Our system is based on color 3D model and thermal 3D model of the target scene generated by KinectFusion using a thermal camera coupled with an RGB-D camera. In off-line phase, Viewpoint Generative Learning (VGL) is applied to the colored 3D model for collecting its stable keypoints descriptors. Those descriptors are utilized in camera pose initialization at the start of on-line phase. After that, our proposed camera tracking which combines frame-to-frame camera tracking with VGL based tacking is performed for accurate estimation of the camera pose. From estimated camera pose, the thermal 3D model is finally superimposed to current mobile camera view. As a result, we can observe the wide area thermal map from any viewpoint. Our system is applied for a temperature change visualization system with a thermal camera coupled with an RGB-D camera and it is also enables the smartphone to interactively display thermal distribution of a given scene.

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“…The cropped visible images are resized to 640×512 resolution through the bicubic interpolation. We made a target board made of materials with different emissivities [40] and then applied the algorithm presented by Zhang et al [41] to compute intrinsic matrices of visible, LWIR, and depth cameras. Finally, we adopted the calibration technique described in [42] to compute extrinsic matrices among multi-modal sensors.…”

Section: Pixel-wise Alignment Of Multispectral Imagesmentioning

confidence: 99%

Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors

Wang¹,

Yang²,

Cao³

et al. 2020

Preprint

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Image Super-Resolution (SR) provides a promising technique to enhance the image quality of low-resolution optical sensors, facilitating better-performing target detection and autonomous navigation in a wide range of robotics applications. It is noted that the state-of-the-art SR methods are typically trained and tested using single-channel inputs, neglecting the fact that the cost of capturing high-resolution images in different spectral domains varies significantly. In this paper, we attempt to leverage complementary information from a low-cost channel (visible/depth) to boost image quality of an expensive channel (thermal) using fewer parameters.To this end, we first present an effective method to virtually generate pixel-wise aligned visible and thermal images based on real-time 3D reconstruction of multi-modal data captured at various viewpoints. Then, we design a feature-level multispectral fusion residual network model to perform high-accuracy SR of thermal images by adaptively integrating co-occurrence features presented in multispectral images. Experimental results demonstrate that this new approach can effectively alleviate the ill-posed inverse problem of image SR by taking into account complementary information from an additional lowcost channel, significantly outperforming state-of-the-art SR approaches in terms of both accuracy and efficiency.

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Visualization of Temperature Change Using RGB-D Camera and Thermal Camera

Cited by 12 publications

References 11 publications

Software Tool for the Extrinsic Calibration of Infrared and RGBD Cameras Applied to Thermographic Inspection

Software Tool for the Extrinsic Calibration of Infrared and RGBD Cameras Applied to Thermographic Inspection

AR Visualization of Thermal 3D Model by Hand-held Cameras

Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors

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