Affine iterative closest point algorithm for point set registration
نویسندگان
چکیده
Article history: Received 24 April 2009 Received in revised form 15 January 2010 Available online 25 January 2010 Communicated by Y. Liu
منابع مشابه
The Iterative Closest Points Algorithm and Affine Transformations
The problem of consistent aligning of 3D point data is known registration task. The most popular registration algorithm is the Iterative Closest Point (ICP) algorithm. One of the main steps of the ICP algorithm is matching. We find a matching in at first time on the basis of the geometric similarity of individual groups of points. It allows to get a good first approximation of the required tran...
متن کاملPoint Set Registration with Integrated Scale Estimation
We present an iterative registration algorithm for aligning two differently scaled 3-D point sets. It extends the popular Iterative Closest Point (ICP) algorithm by estimating a scale factor between the two point sets in every iteration. The presented algorithm is especially useful for the registration of point sets generated by structure-frommotion algorithms, which only reconstruct the 3-D st...
متن کاملLine-to-Point Registration with Applications in Geometric Reconstruction of Coronary Stents
Line-to-Point Registration with Applications in Geometric Reconstruction of Coronary Stents By Claire Y. Lin Registration is a process of geometrically transforming one object to correspond to the other. It can utilized to align images, surfaces, or point clouds. The Iterative Closest Point algorithm is widely used in registration to achieve reconstruction of geometric shapes, but has drawbacks...
متن کاملIterative Closest Point Algorithm in the Presence of Anisotropic Noise
The Iterative closest point (ICP) algorithm is a widely used method for 3D point set registration. It iteratively establishes point correspondences between two input data sets and computes a rigid transformation accordingly. From a statistical point of view, the algorithm implicitly assumes that the points are observed with isotropic Gaussian noise. In this paper, we present the first variant o...
متن کاملPoint-Based Statistical Shape Models with Probabilistic Correspondences and Affine EM-ICP
A fundamental problem when computing statistical shape models (SSMs) is the determination of correspondences between the instances. Often, homologies between points that represent the surfaces are assumed which might lead to imprecise mean shape and variation results. We present a novel algorithm based on the affine Expectation Maximization Iterative Closest Point (EM-ICP) registration method. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Pattern Recognition Letters
دوره 31 شماره
صفحات -
تاریخ انتشار 2010