Fitting Superellipses
نویسنده
چکیده
In the literature, methods for fitting superellipses to data tend to be computationally expensive due to the non-linear nature of the problem. This paper describes and tests several fitting techniques which provide different trade-offs between efficiency and accuracy. In addition, we describe various alternative error of fits (EOF) that can be applied by most superellipse fitting methods. keywords: curve, superellipse, fitting, error measure
منابع مشابه
Equal-Distance Sampling of Superellipse Models
Superellipses are parametric models that can be used for representing two dimensional object parts or aspects of 3-D parts. Previously little care was given to obtaining a precise sampling of the contour of these models. Equal-distance sampling of superellipse model contours is however important for rendering and in cases in which a cost function needs to be estimated for data fitting or parame...
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 کاملLeft Ventricle Volume Measurement on Short Axis MRI Images Using a Combined Region Growing and Superellipse Fitting Method
Segmentation and volume measurement of the cardiac ventricles is an important issue in cardiac disease diagnosis and function assessment. Cardiac Magnetic Resonance Imaging (CMRI) is the current reference standard for the assessment of both left and right ventricular volumes and mass. Several methods have been proposed for segmentation and measurement of cardiac volumes like deformable models, ...
متن کاملTraining PDMs on Models: The Case of Deformable Superellipses
This paper addresses the following problem: How can we make a complicated mathematical shape model simpler while keeping a comparable level of representational power? The proposed solution is to use the original model itself { which represents a class of shapes { to train a Point Distribution Model. In this paper the idea is applied to the case of deformable superellipses.
متن کاملA Neural Architecture for Segmentation and Modelling of Range Data
A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural stages: a SOM is used to perform data segmentation, and, for each segment, a multilayer feed-forward network performs model estimation. The topologypreserving nature of the SOM algorithm makes this architecture 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
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:
- IEEE Trans. Pattern Anal. Mach. Intell.
دوره 22 شماره
صفحات -
تاریخ انتشار 2000