基于细节层次与最小生成树的三维地形识别与检索

图像、视频、音频和图形等均是多媒体数据流中的信息载体,对上述数据所蕴涵的内容进行分析,可以极大地方便人们对它们的使用与管理.基于内容的图像(视频)和音频检索已经取得了不少进展,但是对于图形,特别是3D图形进行识别与检索的有效方法还很少见.提出了对相似3D物体识别与检索的算法,在这个算法中,首先使用细节层次模型对3D物体进行三角面片约减,然后提取3D物体的特征.由于所提取的特征维数很大,最小生成树(minimum spanning tree,简称MST)被用来对每一个3D物体的特征进行约减,基于约减后的特征,实现了基于支持向量机的3D物体识别与检索方法.这个算法被使用到3D丘陵与山地的地形识别中,取得了良好效果.

Recognition and Retrieval of 3D Terrain Based on Level of Detail and Minimum Spanning Tree

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.