Adaptive hierarchical representation of a point-sampled 3d model for fast rendering

A multiresolution hierarchical representation of a 3D model is efficient for fast rendering. A hierarchy is usually constructed by regular subdivision of the bounding volume of a model, it is prone to non-adaptive to the irregular spatial distribution of sample points, and it may affect the quality of rendering. In this paper we present an approach to build up an adaptive hierarchical representation for a point-sampled 3D model. The binary space partition is used to recursively split a point-sampled model according to the principal component analysis of its sample points. Thus a model is subdivided along the direction of the greatest variation, and the partition is adaptive to the spatial distribution of its sample points. A multiresolution hierarchy based on bounding spheres is constructed for a model after this adaptive subdivision. We have constructed adaptive multiresolution hierarchies for several point-sampled models and display them based on the splatting. Experimental results show this approach is efficient for rendering complex point-based 3D models