Self-Calibration from Image Triplets

We describe a method for determining a ne and metric calibration of a camera with unchanging internal parameters undergoing planar motion. It is shown that a ne calibration is recovered uniquely, and metric calibration up to a two fold ambiguity. The novel aspects of this work are: rst, relating the distinguished objects of 3D Euclidean geometry to xed entities in the image; second, showing that these xed entities can be computed uniquely via the trifocal tensor between image triplets; third, a robust and automatic implementation of the method. Results are included of a ne and metric calibration and structure recovery using images of real scenes.