Abstract
In this text we show how points, point pairs, lines, planes, circles, spheres, and rotation, translation and dilation operators and their uncertainty can be evaluated from uncertain data in a unified manner using the Geometric Algebra of conformal space. This extends previous work by Förstner et al. [3] from points, lines and planes to non-linear entities and operators, while keeping the linearity of the estimation method. We give a theoretical description of our approach and show the results of some synthetic experiments.
This work has been supported by DFG grant SO-320/2-3.
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Perwass, C., Gebken, C., Sommer, G. (2005). Estimation of Geometric Entities and Operators from Uncertain Data. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds) Pattern Recognition. DAGM 2005. Lecture Notes in Computer Science, vol 3663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550518_57
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DOI: https://doi.org/10.1007/11550518_57
Publisher Name: Springer, Berlin, Heidelberg
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