Fitting quadrics with a Bayesian prior

作     者：Daniel Beale Yong-Liang Yang Neill Campbell Darren Cosker Peter Hall 

作者机构：University of Bath 

出 版 物：《Computational Visual Media》 (计算可视媒体（英文版）)

年 卷 期：2016年第2卷第2期

页      面：107-117页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Engineering and Physical Sciences Research Council  EPSRC  (EP/K02339X/1  EP/M023281/1) 

主　　题：geometry statistics graphics computer vision 

摘      要：Quadrics are a compact mathematical formulation for a range of primitive surfaces. A problem arises when there are not enough data points to compute the model but knowledge of the shape is available. This paper presents a method for fitting a quadric with a Bayesian prior. We use a matrix normal prior in order to favour ellipsoids when fitting to ambiguous data. The results show the algorithm copes well when there are few points in the point cloud,competing with contemporary techniques in the area.