Progressive Splatting

Abstract

Surface splatting enables high quality and efficient rendering algorithms for dense point-sampled datasets. However, with increasing data complexity, the need for multiresolution models becomes evident. For triangle meshes, progressive or continuous level of detail hierarchies have proven to be very effective when it comes to (locally) adapt the resolution level of the 3D model to the application-dependent quality requirements. In this paper we transfer this concept to splat-based geometry representations. Our progressive splat decimation procedure uses the standard greedy approach but unlike previous work, it uses the full splat geometry in the decimation criteria and error estimates, not just the splat centers. With two improved error metrics, this new greedy framework offers better approximation quality than other progressive splat decimators. It comes even close to the recently proposed globally optimized single-resolution sub-sampling techniques while being faster by a factor of 3.