Rimon Elias

Papers

Total Citations

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About

Rimon Elias is a researcher in computer vision and robotics, with a primary focus on obstacle detection, 3D reconstruction, and autonomous navigation. His work addresses the challenge of enabling robots to perceive and interact with their environment using minimal sensory input—often just a single camera. In his most cited paper, "Wide baseline obstacle detection and localization" (2003, 9 citations), Elias proposed a novel algorithm that matches feature points across widely separated images using an overhead view transformation, allowing an autonomous robot to accurately locate obstacles on a ground plane. This contribution is significant for its practical approach to improving robot autonomy in unstructured environments. His subsequent thesis, "Towards obstacle reconstruction through wide baseline set of images" (2004, 2 citations), extends this work by developing methods to extract 3D information from multiple images, aiding teleoperation tasks where a human operator plans a robot’s virtual path. Though his citation counts are modest, Elias’s research represents foundational work in wide baseline vision and obstacle reconstruction, offering valuable insights for students and researchers interested in low-cost, camera-based robotic perception systems.