Visual quality control of planar working pieces: a curve based approach using prototype fitting
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part IV
A localization framework under non-rigid deformation for robotic surgery
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
A coarse-to-fine IP-driven registration for pose estimation from single ultrasound image
Computer Vision and Image Understanding
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Representing 2D and 3D data sets with implicit polynomials (IPs) has been attractive because of its applicability to various computer vision issues. Therefore, many IP fitting methods have already been proposed. However, the existing fitting methods can be and need to be improved with respect to computational cost for deciding on the appropriate degree of the IP representation and to fitting accuracy, while still maintaining the stability of the fit. We propose a stable method for accurate fitting that automatically determines the moderate degree required. Our method increases the degree of IP until a satisfactory fitting result is obtained. The incrementability of QR decomposition with Gram-Schmidt orthogonalization gives our method computational efficiency. Furthermore, since the decomposition detects the instability element precisely, our method can selectively apply ridge regression-based constraints to that element only. As a result, our method achieves computational stability while maintaining fitting accuracy. Experimental results demonstrate the effectiveness of our method compared with prior methods.