Features Preserving Mesh Simplification

With the rapid development of computer software and hardware technology, mesh was gradually used in various fields. These areas include film and animation, cartography, virtual reality, computer vision, computer graphics, computer-aided geometric design, finite element method, computational geometry, and so on. Technological advances in the development of 3D modeling and 3D scanner technology, making the accuracy of the model increasingly high, which have made a challenge to the storing, processing, rendering, and transmission capability of the computer. Contradictions between limited computer resources and highly sophisticated details of the model have become increasingly prominent. Therefore for efficiency considerations, we often need some simplified model. It is a compromise to simplify the model before processing or rendering. The main purpose of this paper is to propose a method based on quadratic error metric mesh simplification algorithm, which overcoming the shortcoming of traditional simplification algorithm based on local features. It can maintains the overall features of the mesh more effectively during the simplification. Research of this paper mainly includes the following aspects: Firstly, this paper describes the application of mesh simplification algorithm in various fields. The current research at home and abroad were classified and summarized. Then related technology in current mesh simplification algorithm is summarized, at the same time, the advantages and disadvantages of these technologies are analyzed. At last, comparison of two methods to assess effect of mesh simplification will be made and the scope of each will be given. Secondly, it has become a common problem among current mesh simplification that mesh often was simplified uniformly and the global features usually loss in the result. To solve this common problem, we propose a method to detect the global salient geometry features. Then based on which a new mesh simplification algorithm is proposed. Finally, due to the increasingly popular appearance of models with property, simplification algorithm with attributes is meaningful. It is necessary to consider the error of property during simplification. For the calculation of attribute error, this paper improves the non-uniform of RGB space creatively, making the assessment of the property error more accurate. At the same time, a method of salient property features detection was proposed. Based on this, method of salient property features preserving mesh simplification was proposed.