Authors:
Kazuki Matsumoto
1
;
Wataru Nakagawa
1
;
Hideo Saito
1
;
Maki Sugimoto
1
;
Takashi Shibata
2
and
Shoji Yachida
2
Affiliations:
1
Graduate School of Science and Technology, Keio University and, Japan
;
2
NEC Corporation, Japan
Keyword(s):
3D Model, Augmented Reality, Temperature, RGB-D Camera, Thermal Camera, Camera Tracking, Viewpoint Generative Learning.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Applications
;
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image-Based Modeling
;
Mobile Imaging
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Robotics
;
Software Engineering
;
Video Surveillance and Event Detection
Abstract:
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 inte
ractively display thermal distribution of a given scene.
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