Mateu Sbert

Papers

Total Citations

321

H-Index

About

Mateu Sbert is a leading figure in computer graphics, best known for pioneering the use of information theory to solve fundamental problems in rendering and visualization. His key research areas include viewpoint selection, scene complexity analysis, and global illumination. Sbert’s most celebrated contribution is the introduction of **Viewpoint Entropy** (2001), a groundbreaking concept that quantifies the "goodness" of a viewpoint based on the amount of information it captures. This work, with over 317 citations, has become a cornerstone for applications ranging from computational geometry and robot motion to image-based rendering and graph drawing. Beyond viewpoint selection, Sbert has also explored the **visibility complexity of regions**, using mutual information to define and measure scene complexity in 2D environments. His work bridges theoretical rigor with practical impact, providing tools that allow researchers to automatically select optimal camera angles and assess the informational richness of a scene. Through his innovative fusion of information theory and computer graphics, Sbert has fundamentally shaped how we understand and interact with virtual 3D worlds.