Recognizing 3-D Curves from a Stereo Pair of Images: a Semi-differential Approach

作者: Theo Moons , Eric J. Pauwels , Luc J. Van Gool , Michael H. Brill , Eamon B. Barrett

DOI: 10.1007/978-3-662-03039-4_30

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摘要: This study investigates how the stereo view of a 3-D curve can be characterized in way that is invariant under Euclidean motions curve. Depending on knowledge about and variability parameters stereo-setup, several transformation groups are identified as framework relevant to extraction invariants. The point-derivative exchange principle used construct new set semi-differential invariants for pairs. resulting range from quite simple rather complicated, but information needed their computation remains limited at all times. Finally, motion sequences well surface shape descriptors proposed special cases.

参考文章(6)
Luc J. Van Gool, Eric Pauwels, Theo Moons, André Oosterlinck, Semi-differential invariants Geometric invariance in computer vision. pp. 157- 192 ,(1992)
Michael H. Brill, Eamon B. Barrett, Paul M. Payton, Projective invariants for curves in two and three dimensions Geometric invariance in computer vision. pp. 193- 214 ,(1992)
Luc J. Van Gool, Michael H. Brill, Eric Pauwels, Eamon B. Barrett, Theo Moons, Semi-differential invariants for nonplanar curves Geometric invariance in computer vision. pp. 293- 309 ,(1992)
Joseph L. Mundy, Andrew Zisserman, Geometric invariance in computer vision MIT Press. ,(1992)
Eyal Kishon, Trevor Hastie, Haim Wolfson, 3-D curve matching using splines Journal of Robotic Systems. ,vol. 8, pp. 723- 743 ,(1991) , 10.1002/ROB.4620080602
Ralph E. Walde, Arthur A. Sagle, Introduction to Lie groups and Lie algebras ,(1973)