The whole scheme design on 3D model retrieval

Zuojun Liu, Lihong Li
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Abstract

The essence of 3D model retrieval is to classify and to sort. An algorithm based on neural network is proposed in this paper. After pretreatment, six projection viewpoints are selected to project the 3D model in order to generate six two-dimensional images. Then the images are transformed by Fourier Transform to obtain the vector features. Finally, the dimension of vector is compressed to input into neural network to retrieve. The advantage of neural network is to provide an interface between the system and the users. Users can retrieve more than one times if not satisfied. Proved by experiments, the algorithm can get better performance and satisfactory efficiency.
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整个方案设计以三维模型检索为核心
三维模型检索的本质是分类和排序。本文提出了一种基于神经网络的算法。预处理后,选择6个投影视点对三维模型进行投影,生成6幅二维图像。然后对图像进行傅里叶变换,得到图像的矢量特征。最后,将向量的维数压缩后输入神经网络进行检索。神经网络的优点是在系统和用户之间提供了一个接口。如果用户不满意,可以多次检索。实验证明,该算法具有较好的性能和较好的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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