Shoji Yachida

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

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.

Application of LSD-SLAM for visualization temperature in wide-area environment

In this paper, we propose a method to generate a three-dimens ional (3D) thermal map by overlaying thermal images onto a 3D surface reconstructed by a monocular RGB cam era. In this method, we capture the target scene moving both an RGB camera and a thermal camera, which ar e mounted on the same zig. From the RGB image sequence, we reconstruct 3D structures of the scen e by using Large-Scale Direct Monocular Simultaneous Localization and Mapping (LSD-SLAM), on whic h temperature distribution captured by the thermal camera is overlaid, thus generate a 3D thermal map. T he geometrical relationship between those cameras is calibrated beforehand by using a calibration boa rd th t can be detected by both cameras. Since we do not use depth cameras such as Kinect, the depth of the targe t scene is not limited by the measurement range of the depth camera; any depth range can be captured. To demon strating this technique, we show synthesized 3D thermal maps for both indoor and outdoor scenes.