RT info:eu-repo/semantics/article
T1 Calibration of a stereoscopic vision system in the presence of errors in pitch angle
A1 Sigut Saavedra, Marta
A1 Felipe, Jonatán
A1 Acosta Sánchez, Leopoldo
A2 Ingeniería Informática y de Sistemas
K1 calibration
K1 machine learning
K1 U-V disparity
K1 3D scenes reconstruction
AB This paper proposes a novel method for the calibration of a stereo camera system usedto reconstruct 3D scenes. An error in the pitch angle of the cameras causes the reconstructed sceneto exhibit some distortion with respect to the real scene. To do the calibration procedure, whosepurpose is to eliminate or at least minimize said distortion, machine learning techniques have beenused, and more specifically, regression algorithms. These algorithms are trained with a large numberof vectors of input features with their respective outputs, since, in view of the application of theprocedure proposed, it is important that the training set be sufficiently representative of the varietythat can occur in a real scene, which includes the different orientations that the pitch angle can take,the error in said angle and the effect that all this has on the reconstruction process. The most efficientregression algorithms for estimating the error in the pitch angle are derived from decision trees andcertain neural network configurations. Once estimated, the error can be corrected, thus making thereconstructed scene appear more like the real one. Although the authors base their method on U-Vdisparity and employ this same technique to completely reconstruct the 3D scene, one of the mostinteresting features of the method proposed is that it can be applied regardless of the technique usedto carry out said reconstruction.
YR 2022
FD 2022
LK http://riull.ull.es/xmlui/handle/915/34799
UL http://riull.ull.es/xmlui/handle/915/34799
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 16-may-2024