Terrain Simplification Research in Augmented Scene Modeling

作     者：Ming Delie You Kefei Tian Jinwen Liu Jian State Key Laboratory for Image Processing and Intelligent Control, Institute for Pattern Recognition and Artificial Intelligence , Huazhong University of Science and Technology , Wuhan 430074 Wang Guangju 

作者机构：State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074 

出 版 物：《Journal of China University of Geosciences》 (中国地质大学学报（英文版）)

年 卷 期：2001年第12卷第4期

页      面：351-355页

核心收录：

学科分类：08[工学] 081601[工学-大地测量学与测量工程] 0816[工学-测绘科学与技术] 

基　　金：This paper is supported by the State Key Laboratory for Image Processing & Intelligent Control (No. TKLJ9903) National Defe 

主　　题：augmented reality scene modeling terrain simplification triangulated irregular network importance measures local entropy. 

摘      要：Augmented reality is the merging of synthetic sensory information into a user s perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the short-sight problem associated with the traditional methods.