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A global calibration method for multiple vision sensors based on multiple targets

The global calibration of multiple vision sensors (MVS) has been widely studied in the last two decades. In this paper, we present a global calibration method for MVS with non-overlapping fields of view (FOVs) using multiple targets (MT). MT is constructed by fixing several targets, called sub-targets, together. The mutual coordinate transformations between sub-targets need not be known. The main procedures of the proposed method are as follows: one vision sensor is selected from MVS to establish the global coordinate frame (GCF). MT is placed in front of the vision sensors for several (at least four) times. Using the constraint that the relative positions of all sub-targets are invariant, the transformation matrix from the coordinate frame of each vision sensor to GCF can be solved. Both synthetic and real experiments are carried out and good result is obtained. The proposed method has been applied to several real measurement systems and shown to be both flexible and accurate. It can serve as an attractive alternative to existing global calibration methods.