%0 Journal Article
%T Range image registration using hybrid genetic algorithm and point to plane distance based measure<br>基于混合遗传算法和点面距离测度的深度像配准*
%A GAO Peng dong
%A PENG Xiang
%A LI A meng
%A LIU Xiao li
%A <br>高鹏东
%A 彭翔
%A 李阿蒙
%A 刘晓利
%J 计算机应用研究
%D 2007
%I 
%X This paper presented a novel approach for precise registration of range images pair with an improved genetic algorithm(GA) and a new error metric based on the point to plane distance. Different to the existed ICP methods, this approach formulated the surface registration as a high dimensional optimization problem. Then combined the strategy of simulated annealing(SA) selection, hill climbing and dynamic parametric space degeneration into a GA to offer much faster convergence and more precise registration. At the same time, employed a new measure based on the point to plane distance as fitness function to evaluate the alignment error, which made the approach more robust. A number of experiments demonstrate that the presented method is insensitive to noises as well as the initial pose estimation and has high precision and fast convergence.
%K genetic algorithm
%K point to plane distance
%K error metric
%K range image registration<br>遗传算法
%K 点面距离
%K 误差测度
%K 深度像配准
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=0B62C885ECA305DCDE4493A38598C09A&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=59906B3B2830C2C5&sid=0954045FA0C6885F&eid=35E8A259891FB32F&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10