Abstract
Abstract. In this work, we discussed how to directly combine thermal infrared image (TIR) and the point cloud without additional assistance from GCPs or 3D models. Specifically, we propose a point-based co-registration process for combining the TIR image and the point cloud for the buildings. The keypoints are extracted from images and point clouds via primitive segmentation and corner detection, then pairs of corresponding points are identified manually. After that, the estimated camera pose can be computed with EPnP algorithm. Finally, the point cloud with thermal information provided by IR images can be generated as a result, which is helpful in the tasks such as energy inspection, leakage detection, and abnormal condition monitoring. This paper provides us more insight about the probability and ideas about the combining TIR image and point cloud.
Highlights
In the Big Data Era, single sensor alone can hardly provide sufficient information about the target
The proposed process is based on the assumption that the thermal infrared images and the point cloud are generated at the same scene at the same time
Since the Thermal infrared (TIR) image recorded by the camera with certain FOV and the device is fixed on the vehicle with a certain orientation, we crop the point clouds based on the car position information at last
Summary
In the Big Data Era, single sensor alone can hardly provide sufficient information about the target. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-2/W7, 2019 PIA19+MRSS19 – Photogrammetric Image Analysis & Munich Remote Sensing Symposium, 18–20 September 2019, Munich, Germany done trying to co-register the thermal infrared image to MLS point clouds for a large scene. To fill this gap, we proposed a method to direct co-register the TIR image and the point cloud by corresponding keypoints. We will draw a conclusion based on the results, and discuss the outlook for the topic
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