Abstract
This study investigates how the stereo view of a 3-D curve can be characterized in a way that is invariant under 3-D Euclidean motions of the curve. Depending on the knowledge about and the variability of the parameters of the stereo-setup, several transformation groups are identified as the framework relevant to the extraction of invariants. The point-derivative exchange principle can be used to construct a new set of semi-differential invariants for stereo pairs. The resulting invariants range from the quite simple to the rather complicated, but the information needed for their computation remains limited at all times. Finally, invariants from motion sequences as well as surface shape descriptors are proposed as special cases.
The support of ESPRIT Basic Research Action EP 6448 ‘VIVA’ and the Post-Doctoral Research Grants (T. Moons and E. Pauwels) of the Katholieke Universiteit Leuven are gratefully acknowledged.
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References
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© 1994 Springer-Verlag Berlin Heidelberg
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Moons, T., Pauwels, E.J., Van Gool, L.J., Brill, M.H., Barrett, E.B. (1994). Recognizing 3-D Curves from a Stereo Pair of Images: a Semi-differential Approach. In: O, YL., Toet, A., Foster, D., Heijmans, H.J.A.M., Meer, P. (eds) Shape in Picture. NATO ASI Series, vol 126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03039-4_30
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DOI: https://doi.org/10.1007/978-3-662-03039-4_30
Publisher Name: Springer, Berlin, Heidelberg
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