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Part of the book series: Advances in Pattern Recognition ((ACVPR))

Abstract

In this chapter we give an account of two different methods to find constraints for the trifocal tensor Т, used in geometric computer vision. We also show how to single out a set of only eight equations that are generically complete, i.e. for a generic choice of Т, they suffice to decide whether Т is indeed trifocal. Note that eight is minimum possible number of constraints.

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References

  1. Alzati, A., Tortora, A.: A geometric approach to the trifocal tensor. To appear

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  2. Hartley, R., Zisserman, A.: Multiple view geometry in computer vision. Cambridge University Press, Cambribge (2000)

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  3. Thrall, R. M., Chandler, J. H.: Ternary trilinear forms in the field of complex numbers. Duke Math. J. 4, 678–690 (1938)

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Correspondence to Alberto Alzati .

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© 2009 Springer-Verlag London Limited

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Alzati, A., Tortora, A. (2009). Constraints for the Trifocal Tensor. In: Aja-Fernández, S., de Luis García, R., Tao, D., Li, X. (eds) Tensors in Image Processing and Computer Vision. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-299-3_12

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  • DOI: https://doi.org/10.1007/978-1-84882-299-3_12

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-298-6

  • Online ISBN: 978-1-84882-299-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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