Robust Parameter Estimation in Computer Vision: Geometric Fitting and Deformable Registration
نویسنده
چکیده
ix
منابع مشابه
Feature-constrained Nonlinear Registration of Lung CT Images
Deformable image registration is a key enabling technology for advanced treatment of lung cancer patients, as it can facilitate motion estimation, structure segmentation, as well as dose tracking and accumulation. In this work, we developed a hybrid feature-constrained deformable registration method and applied it to tackle the EMPIRE10 (Evaluation of Methods for Pulmonary Image Registration 20...
متن کاملHyperaccuracy for Geometric Fitting
A rigorous accuracy analysis is given to various techniques for estimating parameters of geometric models from noisy data. It is first pointed out that parameter estimation for computer vision applications is very different in nature from traditional statistical analysis and that a different mathematical framework is necessary in such a domain. After general theories on estimation and accuracy ...
متن کاملA New Approach to Geometric Fitting
Geometric fitting — parameter estimation for data subject to implicit parametric constraints — is a very common sub-problem in computer vision, used for curve, surface and 3D model fitting, matching constraint estimation and 3D reconstruction under constraints. Although many algorithms exist for specific cases, the general problem is by no means ‘solved’ and has recently become a subject of con...
متن کاملA Robust Nonparametric Estimation Framework for Implicit Image Models
Robust model fitting is important for computer vision tasks due to the occurrence of multiple model instances, and, unknown nature of noise. The linear errors-in-variables (EIV) model is frequently used in computer vision for model fitting tasks. This paper presents a novel formalism to solve the problem of robust model fitting using the linear EIV framework. We use Parzen windows to estimate t...
متن کاملGeometric Robust Watermarking through Mesh Model Based Correction
While geometric attacks are one of the most challenging problems in watermarking, random bending is the most difficult to handle among all geometric attacks. Such attacks are difficult to correct by traditional parameter estimation or registration approaches. In this paper, we present a watermarking scheme based on a deformable mesh model to combat such attacks. The distortion is corrected usin...
متن کامل