The calibration of a multi-camera system for volumetric measurements is a basic requirement of reliable 3D measurements and object tracking. In order to refine the precision of the mapping functions, a new, tomographic reconstruction-based approach is presented. The method is suitable for Volumetric Particle Image Velocimetry (PIV), where small particles, drops or bubbles are illuminated and precise 3D position tracking or velocimetry is applied. The technique is based on the 2D cross-correlation of original images of particles with regions from a back projection of a tomographic reconstruction of the particles. The off-set of the peaks in the correlation maps represent disparities, which are used to correct the mapping functions for each sensor plane in an iterative procedure. For validation and practical applicability of the method, a sensitivity analysis has been performed using a synthetic data set followed by the application of the technique on Tomo-PIV measurements of a jet-flow. The results show that initial large disparities could be corrected to an average of below 0.1 pixels during the refinement steps, which drastically improves reconstruction quality and improves measurement accuracy and reliability.
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