Fitting CAD data to scanned data with large deformation☆
نویسندگان
چکیده
منابع مشابه
Fitting parametric random effects models in very large data sets with application to VHA national data
BACKGROUND With the current focus on personalized medicine, patient/subject level inference is often of key interest in translational research. As a result, random effects models (REM) are becoming popular for patient level inference. However, for very large data sets that are characterized by large sample size, it can be difficult to fit REM using commonly available statistical software such a...
متن کاملFitting semiparametric random effects models to large data sets.
For large data sets, it can be difficult or impossible to fit models with random effects using standard algorithms due to memory limitations or high computational burdens. In addition, it would be advantageous to use the abundant information to relax assumptions, such as normality of random effects. Motivated by data from an epidemiologic study of childhood growth, we propose a 2-stage method f...
متن کاملFitting circles to data with correlated noise
We study the problem of fitting circles to scattered data. Unlike many other studies, we assume that the noise is (strongly) correlated; we adopt a particular model where correlations decay exponentially with the distance between data points. Our main results are formulas for the maximum likelihood estimates and their covariance matrix. Our study is motivated by (and applied to) arcs collected ...
متن کاملFitting surfaces to data with covariances
We are concerned with solving an equation whose form is applicable to a wide class of problems arising in computer vision. The equation typically relates image point locations to the parameters of some appropriate model. We assume that each measured datum is accompanied by a covariance matrix that characterises the uncertainty of the measurement. Noisy data are assumed to be in plentiful supply...
متن کاملSuperellipse fitting to partial data
Superellipses can be used to represent in a compact form a large variety of shapes, and are useful for modelling in the fields of computer graphics and computer vision. However, fitting them to data is difficult and computationally expensive. Moreover, when only partial data is available the parameter estimates become unreliable. This paper attempts to improve the process of fitting to partial ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computational Design and Engineering
سال: 2020
ISSN: 2288-5048
DOI: 10.1093/jcde/qwaa013