Self-calibration from multiple views with a rotating camera
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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ACM Transactions on Sensor Networks (TOSN)
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We present a linear method for self-calibration of a moving rig when no correspondences are available between the cameras. Such a scenario occurs, for example, when the cameras have different viewing angles, different zoom factors or different spectral ranges. It is assumed that during the motion of the rig, the relative viewing angle between the cameras remains fixed and is known. Except for the fixed relative viewing angle, any of the internal parameters and any of the other external parameters of the cameras may vary freely. The calibration is done by linearly computing multilinear invariants, expressing the relations between the optical axes of the cameras during the motion. A solution is then extracted from these invariants. Given the affine calibration, the metric calibration is known to be achieved linearly (e.g. by assuming zero skew). Thus an automatic solution is presented for self calibration of a class of moving rigs with varying internal parameters. This solution is achieved without using any correspondences between the cameras, and requires only solving linear equations.