IEEE Trans Pattern Anal Mach Intell - Shape Representation and Registration in Vector Implicit Spaces: Adopting a Closed Form Solution in the Optimization Process.

Tópicos

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Resumo

In this paper, a novel method to solve the shape registration problem covering both global and local deformations is proposed. The vector distance function (VDF) is used to represent source and target shapes. The problem is formulated as an energy optimization process by matching the VDF's of the source and target shapes. The minimization process results in estimating the transformation parameters for the global and local deformation cases. Gradient descent optimization handles the computation of scaling, rotation, and translation matrices used to minimize the global differences between source and target shapes. Non rigid deformations require a large number of parameters which make the use of the gradient descent minimization a very time consuming process. We propose to compute the local deformation parameters using a closed form solution as a linear system of equations derived from approximating an objective function. Extensive experimental validations and comparisons performed on generalized 2D shape data demonstrate the robustness and effectiveness of the method.

Resumo Limpo

paper novel method solv shape registr problem cover global local deform propos vector distanc function vdf use repres sourc target shape problem formul energi optim process match vdfs sourc target shape minim process result estim transform paramet global local deform case gradient descent optim handl comput scale rotat translat matric use minim global differ sourc target shape non rigid deform requir larg number paramet make use gradient descent minim time consum process propos comput local deform paramet use close form solut linear system equat deriv approxim object function extens experiment valid comparison perform general d shape data demonstr robust effect method

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