Abstract
We describe a method for determining affine and metric calibration of a camera with unchanging internal parameters undergoing planar motion. It is shown that affine calibration is recovered uniquely, and metric calibration up to a two fold ambiguity.
The novel aspects of this work are: first, relating the distinguished objects of 3D Euclidean geometry to fixed entities in the image; second, showing that these fixed 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 affine and metric calibration and structure recovery using images of real scenes.
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© 1996 Springer-Verlag Berlin Heidelberg
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Armstrong, M., Zisserman, A., Hartley, R. (1996). Self-calibration from image triplets. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015519
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DOI: https://doi.org/10.1007/BFb0015519
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