A Research about Adaptive Subdivision Algorithm Based On Doo- Sabin Mode

Subdivision surface method is a series of iterative operation adopts a certain subdivision formula for an initial grid, obtains the smooth limits surface finally, and can dispose any arbitrary complex topology grid. At present most of the subdivision algorithm are 1-4 subdivisions and as the number of subdivision increase, the grid grow so toorapid in the number of patch that it is difficult for the model after subdivision to deal with other things. We proposed an adaptive Doo-Sabin Mode subdivision algorithm to solve this problem, which take the average vector of the vertex and the angle between the intersecting surfaces of the vertex as a measurement criterion. This criterion is used to divide the surface, and then make local subdivision. In this way, when the times of subdivision are fewer (the demand of smoothness is not too high), the effect of subdivision has little difference, but efficiency of the algorithm can be greatly improved. Compared with the normal Doo-Sabin subdivision model, experimental results showed that adaptive Doo-Sabin subdivision algorithm can largely slow the growth speed of the amount of model data on the premise that guarantee the quality of surface.