Simultaneous affine registration of multiple shapes∗
نویسندگان
چکیده
The problem of simultaneously estimating affine deformations between multiple objects occur in many applications. Herein, a direct method is proposed which provides the result as a solution of a linear system of equations without establishing correspondences between the objects. The key idea is to construct enough linearly independent equations using covariant functions, and then finding the solution simultaneously for all affine transformations. Quantitative evaluation confirms the performance of the method.
منابع مشابه
Learning Shape Models from Examples
This paper addresses the problem of learning shape models from examples. The contributions are twofold. First, a comparative study is performed of various methods for establishing shape correspondence based on shape decomposition, feature selection and alignment. Various registration methods using polygonal and Fourier features are extended to deal with shapes at multiple scales and the importa...
متن کاملProbability Density Estimation using Isocontours and Isosurfaces: Application to Information Theoretic Image Registration
We present a new, geometric approach for determining the probability density of the intensity values in an image. We drop the notion of an image as a set of discrete pixels, and assume a piecewise-continuous representation. The probability density can then be regarded as being proportional to the area between two nearby isocontours of the image surface. Our paper extends this idea to joint dens...
متن کاملCompensation of brain shift during surgery using non-rigid registration of MR and ultrasound images
Background: Surgery and accurate removal of the brain tumor in the operating room and after opening the scalp is one of the major challenges for neurosurgeons due to the removal of skull pressure and displacement and deformation of the brain tissue. This displacement of the brain changes the location of the tumor relative to the MR image taken preoperatively. Methods: This study, which is done...
متن کاملRegistration of Multiple Shapes using Constrained Optimal Control
Lagrangian particle formulations of the large deformation diffeomorphic metric mapping algorithm (LDDMM) only allow for the study of a single shape. In this paper, we introduce and discuss both a theoretical and practical setting for the simultaneous study of multiple shapes that are either stitched to one another or slide along a submanifold. The method is described within the optimal control ...
متن کاملNon-rigid motion estimation from hierarchical adaptive local affine registrations
Non-rigid image registrations have been widely employed in medical imaging to estimate the complex tissue deformations such as those caused by respiratory motion. To reduce the computational burden of non-rigid registration techniques, alternative approaches have been proposed which decompose the non-rigid registration problem into a combination of multiple more simple registration problems, su...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012