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软件学报  2003 

Recognition and Retrieval of 3D Terrain Based on Level of Detail and Minimum Spanning Tree
基于细节层次与最小生成树的三维地形识别与检索

Keywords: level of detail,minimum spanning tree,support vector machine,3D retrieval and recognition,feature reduction
细节层次
,最小生成树,支持向量机,3D检索与识别,特征约减

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Abstract:

Image, video, audio and graphics are information media in multimedia. In order to use and manage them effectively, the contents implied by them are needed to analyze. Currently, content-based image (video) and audio retrieval make some progress. However, there is no a very efficient method to perform a similar graphics retrieval, especially a similar 3D graphics retrieval. In this paper, an algorithm is presented to implement the similar 3D object recognition and retrieval. In this algorithm, 3D features are first obtained after the meshes of a 3D object are reduced through level of detail. Since the dimension of the extracted 3D features is very huge, minimum spanning tree (MST) are used to reduce the features, then the recognition of similar 3D objects are realized by Support Vector Machine (SVM). The proposed algorithm works well when it is used to recognize and retrieve a 3D terrain.

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