IEEE Transactions on Pattern Analysis and Machine Intelligence
On using CAD models to compute the pose of curved 3D objects
CVGIP: Image Understanding - Special issue on directions in CAD-based vision
Geometric invariance in computer vision
Geometric invariance in computer vision
3L Fitting of Higher Degree Implicit Polynomials
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
The 3L Algorithm for Fitting Implicit Polynomial Curves and Surfaces to Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rotations, translations and symmetry detection for complexified curves
Computer Aided Geometric Design
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New representations are developed for 2D IP (implicit polynomial) curves of arbitrary degree. These representations permit shape recognition and pose estimation with essentially single, rather than iterative, computation, and extract and use all the information in the polynomial coefficients. This is accomplished by decomposing polynomial coefficient space into a union of orthogonal subspaces for which rotations within two dimensional subspaces or identity transformations within one dimensional subspaces result from rotations in x, y measured-data space. These rotations in the two dimensional coefficient subspaces are related in simple ways to each other and to rotation in the x, y data space. By recasting this approach in terms of complex polynomials, i.e, z = x + iy and complex coefficients, further simplification occurs for rotations and some simplification occurs for translation.