GPU-based Mapping of Thermal Imagery for Generating 3D Occlusion-Aware Point Clouds
Published in IGARSS - IEEE International Geoscience and Remote Sensing Symposium, 2022
Abstract
This work describes an efficient approach for generating large 3D thermal point clouds considering the occlusion of camera viewpoints. For that purpose, RGB and thermal imagery are first corrected and fused with an intensity correlation-based algorithm. Then, absolute temperature values are obtained from the normalized data. Finally, thermal imagery is mapped on the point cloud using the Graphics Processing Unit (GPU) hardware. The proposed occlusion-aware mapping algorithm is massively parallelized using OpenGL’s compute shaders. Our solution allows generating dense thermal point clouds in a lower response time compared with other notable soft-ware solutions (e.g., Agisoft Metashape or Pix4Dmapper) that yield results with a significantly lower point density.
Recommended citation: López, Alfonso and Jurado, Juan M. and Ogayar, Carlos J. and Feito, Francisco R. (2022). GPU-based Mapping of Thermal Imagery for Generating 3D Occlusion-Aware Point Clouds. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium 1460-1463.
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