Reverse Subdivision for Optimizing Visibility Tests
Faramarz F. Samavati - Professor, University of Calgary
Sun, 12-Sep-2021 / 9:00 / Link:
Video Poster


In many game and GIS applications, it is necessary to verify whether two entities are visible over a terrain. This is usually done using line-of-sight algorithms. Performing numerous line-of-sight computations, particularly over a large terrain, can be highly resource-intensive (in run time and/or memory). Terrain simplification methods can be used to reduce the resource impact of the visibility algorithms. To take advantage of the high-speed algorithms for regular terrain models, we introduce regularity-preserving terrain simplification methods based on a novel multiresolution approach designed to maximize visibility test accuracy. Our multiresolution is constructed using a feature-aware reverse subdivision.


Faramarz F. Samavati is a professor of Computer Science at the University of Calgary and the lead of the GIV research team. Dr. Samavati's research interests include Computer Graphics, Visualization, Digital Earth and Geometric Modeling. Dr. Samavati has received a number of awards including seven best paper awards, Digital Alberta Award, Great Supervisor Award, University of Calgary Peak Award, Association for Computing Machinery (ACM) Recognition of Service Award, and Faculty of science's Scholarship Excellence Award. Dr. Samavati was one of the finalists of ASTech Award (Alberta's highest Science and Technology honours), for Outstanding Leadership in Alberta Technology in 2017.