Abbas Rafii

Papers

Total Citations

121

H-Index

About

Abbas Rafii is a leading researcher in computer vision and 3D geometric modeling, best known for his pioneering work on robust plane fitting from noisy range data. His most influential contribution, the CC-RANSAC algorithm, introduced a novel approach to simultaneously fitting multiple planar surfaces in cluttered point clouds, overcoming the limitations of traditional RANSAC by leveraging connectivity constraints. This work, published in 2010 and now with over 120 citations, has become a foundational method for tasks ranging from autonomous navigation to heritage preservation. Rafii’s research addresses core challenges in extracting meaningful geometric primitives from real-world sensor data, enabling more reliable scene understanding and reconstruction. His contributions have been widely adopted in robotics, computer graphics, and remote sensing communities. Beyond this landmark paper, Rafii continues to advance algorithms for efficient and accurate 3D perception, making his work essential reading for students and researchers tackling problems in spatial data analysis and model fitting.