翻訳と辞書 Words near each other ・ Pointe d'Otemma ・ Pointe d'Uble ・ Pointe de Barasson ・ Pointe de Bellevue ・ Point Roberts, Washington ・ Point Robinson ・ Point Robinson Light ・ Point Rock, New York ・ Point Sal State Beach ・ Point Salubrious Historic District ・ Point Samson, Western Australia ・ Point San Luis Light ・ Point San Pablo Yacht Harbor ・ Point San Quentin ・ Point Sebago Resort ・ Point set registration ・ Point set triangulation ・ Point shaving ・ Point Sherman Light ・ Point shooting ・ Point Smellie ・ Point source ・ Point source (disambiguation) ・ Point source pollution ・ Point South, South Carolina ・ Point Southworth ・ Point spread function ・ Point Stadium ・ Point State Park ・ Point Stephens Light Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Point set registration ： ウィキペディア英語版 Point set registration In computer vision and pattern recognition, point set registration, also known as point matching, is the process of finding a spatial transformation that aligns two point sets. The purpose of finding such a transformation includes merging multiple data sets into a globally consistent model, and mapping a new measurement to a known data set to identify features or to estimate its pose. A point set may be raw data from 3D scanning or an array of rangefinders. For use in image processing and feature-based image registration, a point set may be a set of features obtained by feature extraction from an image, for example corner detection. Point set registration is used in optical character recognition〔 and aligning data from magnetic resonance imaging with computer aided tomography scans. == Overview of problem == The problem may be summarized as follows: Let $\backslash lbrace\backslash mathcal,\backslash mathcal\backslash rbrace$ be two finite size point sets in a finite-dimensional real vector space $\backslash mathbb^d$, which contain $M$ and $N$ points respectively. The problem is to find a transformation to be applied to the moving "model" point set $\backslash mathcal$ such that the difference between $\backslash mathcal$ and the static "scene" set $\backslash mathcal$ is minimized. In other words, a mapping from $\backslash mathbb^d$ to $\backslash mathbb^d$ is desired which yields the best alignment between the transformed "model" set and the "scene" set. The mapping may consist of a rigid or non-rigid transformation. The transformation model may be written as $T$ where the transformed, registered model point set is: It is useful to define an optimization parameter $\backslash theta$: such that it is clear that the optimizing algorithm adjusts $\backslash theta$. Depending on the problem and number of dimensions, there may be more such parameters. The output of a point set registration algorithm is therefore the transformation parameter $\backslash theta$ of model $T$ so that $\backslash mathcal$ is optimally aligned to $\backslash mathcal$. In convergence, it is desired for the distance between the two point sets to reach a global minimum. This is difficult without exhausting all possible transformations, so a local minimum suffices. The distance function between a transformed model point set $T(\backslash mathcal)$ and the scene point set $\backslash mathcal$ is given by some function $\backslash operatorname$. A simple approach is to take the square of the Euclidean distance for every pair of points: (m - s)^2|}} Minimizing such a function in rigid registration is equivalent to solving a least squares problem. However, this function is sensitive to outlier data and consequently algorithms based on this function tend to be less robust against noisy data. A more robust formulation of the cost function uses some ''robust function'' $g$: (T(\mathcal), \mathcal) = \sum_ \sum_} Such a formulation is known as an ''M-estimator''. The robust function $g$ is chosen such that the local configuration of the point set is insensitive to distant points, hence making it robust against outliers and noise.〔 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Point set registration」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.