The visualization of large amounts of particles, glyphs, and other point-based data plays an important role in many fields of science, among them flow mechanics, molecular dynamics, and medical imaging. The proper perception of spatial structures and spatial relations in the data is crucial to the understanding. To accommodate this aspect, we utilize and improve an existing ambient occlusion approach, originally tailored towards line rendering and extend the approach to be applicable to point-based visualizations.