A Novel Kernel Correlation Model with the Correspondence Estimation

作者：Chen Pengwen^*

来源：Journal of Mathematical Imaging and Vision, 2011, 39(2): 100-120.

DOI：10.1007/s10851-010-0230-6

• Hellinger distance
• Kernel correlation
• Monge Kantorovich mass transport problem
• Point set registration

We present a novel multiple-linked iterative closest point method to estimate correspondences and the rigid/non-rigid transformations between point-sets or shapes. The estimation task is carried out by maximizing a symmetric similarity function, which is the product of the square roots of correspondences and a kernel correlation. The local mean square error analysis and robustness analysis are provided to show our method's superior performance to the kernel correlation method.

• 出版日期2011-2