Bahman Soheilian

Paris-Est Sup, Institut national de l’information géographique et forestière

Papers

Total Citations

H-Index

About

Bahman Soheilian’s research lies at the intersection of autonomous navigation, 3D urban modeling, and computer vision, with a focus on enabling robots and vehicles to perceive and move through dense city environments. His work has made significant contributions to vision-based localization, particularly through the evaluation of feature extractors like SIFT and SURF for interest point detection—a critical step for robust navigation without GPS. Soheilian has also advanced the generation of integrated 3D city models that incorporate visual landmarks, providing autonomous systems with actionable, drivable trajectories that account for obstacles and dynamic traffic. In the realm of point cloud processing, he developed methods to extract outlined planar clusters of street facades from terrestrial laser data acquired by Mobile Mapping Systems, offering valuable tools for digital mapping and robotics. With each of his top-cited papers garnering between 13 and 14 citations, his work has steadily influenced the fields of urban autonomy and geospatial analysis. Soheilian’s contributions are especially notable for bridging the gap between raw sensor data and practical navigation solutions, making him a key figure in the development of smarter, safer autonomous systems for complex urban landscapes.