A Dynamic Method for Generating Multi-Resolution TIN Models
Author(s) -
Bisheng Yang,
Wenzhong Shi,
Qingquan Li
Publication year - 2005
Publication title -
photogrammetric engineering and remote sensing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 127
eISSN - 2374-8079
pISSN - 0099-1112
DOI - 10.14358/pers.71.8.917
Subject(s) - triangulated irregular network , vertex (graph theory) , computer science , tin , resolution (logic) , visualization , enhanced data rates for gsm evolution , mean squared error , algorithm , data mining , artificial intelligence , mathematics , theoretical computer science , remote sensing , geography , digital elevation model , statistics , materials science , metallurgy , graph
It is essential to generate multi-resolution Triangulated Irregular Network (TIN) models dynamically and efficiently in three-dimensional (3D) visualization, virtual reality, and geographic information systems (GIS), because the data that needs to be processed is multiple in scale and large in volume. This paper proposes a new method, which extends the edge collapse and vertex split algorithms, to dynamically generate a multi-resolution TIN models. in contrast to previous approaches, a new method is proposed to encode and store vertex dependency relationships in the multi-resolution model. As a result, the validity of vertex splits and edge collapses is improved; the efficiency of storing data is also enhanced by the proposed method. To evaluate the performance of the proposed method, we further extend the assessment to (a) time cost; (b) the quality of the multi-resolution TIN model; and (c) the view-dependent multi-resolution model. The root mean square error (RMSE) of the elevation of the vertex and the quality of the shape of the triangle are adopted to evaluate the quality of a generated multi-resolution TIN model. The results of the experiment demonstrate that the proposed method performs better than previous methods in terms of time cost, and can achieve multi-resolution TIN models with a higher accuracy.
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