Point sampling with uniformly distributed lines

In this paper we address the problem of extracting representative point samples from polygonal models. The goal of such a sampling algorithm is to find points that are evenly distributed. We propose star-discrepancy as a measure for sampling quality and propose new sampling methods based on global line distributions. We investigate several line generation algorithms including an efficient hardware-based sampling method. Our method contributes to the area of point-based graphics by extracting points that are more evenly distributed than by sampling with current algorithms

River Conservation: Going against the Flow to Meet Global Challenges

Rivers are among the most diverse and threatened ecosystems on Earth, as they are impacted by increasing human pressures. Because rivers provide essential goods and services, conservation of these ecosystems is a requisite for sustainable development. Therefore, we must seek ways to conserve healthy rivers and to restore degraded ones