TY - JOUR
T1 - Generation of Thermal Point Clouds From Uncalibrated Thermal Infrared Image Sequences and Mobile Laser Scans
AU - Zhu, Jingwei
AU - Xu, Yusheng
AU - Hoegner, Ludwig
AU - Stilla, Uwe
N1 - Publisher Copyright:
© 1963-2012 IEEE.
PY - 2023
Y1 - 2023
N2 - Monitoring building efficiency is a hot topic for engineers and researchers. Thermal infrared (TIR) images describe thermal attributes but require professional knowledge for analysis. Moreover, images can hardly describe the thermal attributes of the buildings in all aspects. Therefore, as-built thermal point clouds become the solution. In this case, geometric distortions of TIR images cannot be neglected. To generate the thermal point clouds with TIR image sequences, we propose to use mobile laser scanning (MLS) point clouds as control point sets for calibration and a workflow for the thermal point cloud generation. To begin with, intensity images are generated from the point clouds, and corresponding points are detected from the TIR image and intensity image frame. Moreover, the intrinsic parameters are estimated with corresponding points. Finally, the thermal point clouds are generated with calibrated TIR images and MLS point clouds. The result demonstrates that the automatic method can achieve comparable or even better calibration results than the manual method.
AB - Monitoring building efficiency is a hot topic for engineers and researchers. Thermal infrared (TIR) images describe thermal attributes but require professional knowledge for analysis. Moreover, images can hardly describe the thermal attributes of the buildings in all aspects. Therefore, as-built thermal point clouds become the solution. In this case, geometric distortions of TIR images cannot be neglected. To generate the thermal point clouds with TIR image sequences, we propose to use mobile laser scanning (MLS) point clouds as control point sets for calibration and a workflow for the thermal point cloud generation. To begin with, intensity images are generated from the point clouds, and corresponding points are detected from the TIR image and intensity image frame. Moreover, the intrinsic parameters are estimated with corresponding points. Finally, the thermal point clouds are generated with calibrated TIR images and MLS point clouds. The result demonstrates that the automatic method can achieve comparable or even better calibration results than the manual method.
KW - Geometric calibration
KW - thermal point clouds
UR - http://www.scopus.com/inward/record.url?scp=85162667209&partnerID=8YFLogxK
U2 - 10.1109/TIM.2023.3284942
DO - 10.1109/TIM.2023.3284942
M3 - Article
AN - SCOPUS:85162667209
SN - 0018-9456
VL - 72
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
M1 - 1005916
ER -