摘要
三维模型检索的实质就是对模型进行分类和排序,据此提出一种基于神经网络的三维模型检索算法.对三维模型进行预处理后,选择六个投影视点把模型透视投影成六幅二维图像,通过两次一维傅里叶变换在频域提取模型的高维向量特征,并在压缩成六维后输入到神经网络实现模型的检索.神经网络方法的优势是能提供一个系统和用户的动态交互接口,用户对检索结果不满意可以多次检索.经测试数据库的实验结果表明,该算法具有很好的检索性能和较高的检索效率.
The essential 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 users.Users can retrieve more than one times if not satisfied.Proved by experiment,the algorithm can get better performance and better efficiency.
出处
《湖南工程学院学报（自然科学版）》
2010年第4期47-51,共5页
Journal of Hunan Institute of Engineering(Natural Science Edition)
基金
淮阴工学院青年基金项目(HGXK0707)
关键词
预处理
透视投影
傅立叶变换
压缩
神经网络
pretreatment
perspective projection
Fourier Transform
compression
neural network
