A method for automatic classification of 3D models based on adaboost

Abstract

The invention provides an AdaBoost-based 3D (three-dimensional) model automatic classification method. The AdaBoost-based 3D model automatic classification method comprises the following steps of: calculating approximate geodesic distances of any two top points of a 3D model; forming an affine matrixe of the 3D model according to the calculated approximate geodesic distances of any two top points of the 3D model; simulating the affine matrix containing all top point relationships through an approximation method; resolving the affine matrix through Jacobi method characteristics; sorting the obtained characteristic values from large to small in sequence; taking the second to the twenty-first (in total 20) characteristic values as descriptors of the 3D model; and using an AdaBoost method to classify the 3D model. By the AdaBoost-based automatic 3D model classification method, automatic characteristic extraction of the 3D model is realized, and 3D model automatic classification is carried out by using the characteristics; and compared with the prior art, the AdaBoost-based automatic 3D model classification method has the characteristics of high classification precision and wide application range.

Description

technical field [0001] The invention relates to an automatic classification method of three-dimensional models. Background technique [0002] As the fourth-generation multimedia data type after sound, image and video, 3D model is the most intuitive and expressive multimedia information. With the rapid development of laser scanning technology and network technology, the creation and application of 3D models are becoming more and more extensive, and the resources of 3D models are becoming more and more abundant. The increase of enterprise product types and varieties and the expansion of product data scale make the classification research of 3D models in product design have important theoretical and engineering significance. As an emerging research hotspot in the field of computer graphics, shape-based 3D model classification has gained extensive attention in various fields such as model design of industrial products, virtual reality, simulation, 3D games, computer vision, mol...

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Problems solved by technology

[0005] (1) The 3D model classification method based on Bayesian aggregation is mainly for classifying 3D models belonging to the hierarchical structure, which has certain limitations and a small scope of application;

[0006] (2) The 3D model classification method based on neural network has low classification accuracy and low classification accuracy

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