Automated thermal 3 D reconstruction based on a robot equipped with uncalibrated infrared stereovision cameras

Thierry Sentenac 1, 2 Florian Bugarin 1 Benoit Ducarouge 2 Michel Devy 2
2 LAAS-RAP - Équipe Robotique, Action et Perception
LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse]
Abstract : In many industrial sectors, Non Destructive Testing (NDT) methods are used for the thermomechanical analysis of parts in assemblies of engines or reactors or for the control of metal forming processes. This article suggests an automated multi-view approach for the thermal 3D reconstruction required in order to compute 3D surface temperature models. This approach is based only on infrared cameras mounted on a Cartesian robot. The low resolution of these cameras associated to a lack of texture to infrared images require to use a global approach based first on an uncalibrated rectification and then on the simultaneous execution, in a single step, of the dense 3D reconstruction and of an extended self-calibration. The uncalibrated rectification is based on an optimization process under constraints which calculates the homographies without prior calculation of the Fundamental Matrix and which minimizes the projective deformations between the initial images and the rectified ones. The extended self-calibration estimates both the parameters of virtual cameras that could provide the rectified images directly, and the parameters of the robot. It is based on two criteria evaluated according to the noise level of the infrared images. This global approach is validated through the reconstruction of a hot object against a reference reconstruction acquired by a 3D scanner.
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Contributeur : Florian Bugarin <>
Soumis le : mercredi 4 juillet 2018 - 09:38:13
Dernière modification le : mercredi 11 juillet 2018 - 11:29:30



Thierry Sentenac, Florian Bugarin, Benoit Ducarouge, Michel Devy. Automated thermal 3 D reconstruction based on a robot equipped with uncalibrated infrared stereovision cameras. Advanced Engineering Informatics, Elsevier, 2018, 38, pp.203 - 215. 〈〉. 〈10.1016/j.aei.2018.06.008〉. 〈hal-01829409〉



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