Sequential point trees provide the state-of-the-art technique for rendering point models, by re-arranging hierarchical points sequentially according to geometric errors running on GPU for fast rendering. This paper pr...Sequential point trees provide the state-of-the-art technique for rendering point models, by re-arranging hierarchical points sequentially according to geometric errors running on GPU for fast rendering. This paper presents a view dependent method to augment sequential point trees by embedding the hierarchical tree structures in the sequential list of hierarchical points. By the method, two kinds of indices are constructed to facilitate the points rendering in an order mostly from near to far and from coarse to fine. As a result, invisible points can be culled view-dependently in high efficiency for hardware acceleration, and at the same time, the advantage of sequential point trees could be still fully taken. Therefore, the new method can run much faster than the conventional sequential point trees, and the acceleration can be highly promoted particularly when the objects possess complex occlusion relationship and viewed closely because invisible points would be in a high percentage of the points at finer levels.展开更多
基金A preliminary version of this paper appeared in Proc. Pacific Graphics 2005, Macao. The work is supported by the National Basic Research 973 Program of China （Grant No. 2002CB312102）, the National Natural Science Foundation of China （Grant Nos. 60373051, 60473105） and the Research Grant of the University of Macao.
文摘Sequential point trees provide the state-of-the-art technique for rendering point models, by re-arranging hierarchical points sequentially according to geometric errors running on GPU for fast rendering. This paper presents a view dependent method to augment sequential point trees by embedding the hierarchical tree structures in the sequential list of hierarchical points. By the method, two kinds of indices are constructed to facilitate the points rendering in an order mostly from near to far and from coarse to fine. As a result, invisible points can be culled view-dependently in high efficiency for hardware acceleration, and at the same time, the advantage of sequential point trees could be still fully taken. Therefore, the new method can run much faster than the conventional sequential point trees, and the acceleration can be highly promoted particularly when the objects possess complex occlusion relationship and viewed closely because invisible points would be in a high percentage of the points at finer levels.
