期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：46
期号：1
页码：098-102
出版社：Journal of Theoretical and Applied
摘要：Aim at solving the existing problems of 3D model retrieval based on neural network, this paper proposes a new algorithm based on BP-bagging. Through bagging, the algorithm turns the weak classifier into the strong. As to feature extraction, the algorithm projections 3D model into six 2D images by six perspective points. Then transforms the images into frequency domain, gets the high dimension feature by two 1D Fourier Transformation, and compress the high dimension feature to the lower, inputs into the BP-bagging classifier to retrieval the 3D model. Proved by the experiment, the new algorithm is more effective in 3D model retrieval.
关键词：3D Model Retrieval; BP-bagging Classifier; Feature Extraction; Compression
