Balanced Tilling Based Out-of-Core Simplification
Cai Kang · Chinese Journal of Computers · 2002
All the existing adaptable out of core simplification algorithms need to scan the original model more than one time. So the algorithm efficiency is relatively lower when comparing with uniform sampling approaches. This paper presents an adaptive clustering method, called Balanced Tiling (BT), for out of core simplification, which only needs one pass over the input model. The key idea behind BT is that the model surface can be recorded using surface coding and the global distribution of surface details can be obtained through quadric quantizing of the original model. The algorithm presented in this paper can position all types of detail areas, while some other out of core simplification approaches can only position feature edges. The detail areas will be restored while smooth areas will be further simplified. BT especially suits handling super large models because the I/O time is saved greatly. The memory requirement is small, which is only related with the size of the output model