Tobias Feldmann

Papers

Total Citations

H-Index

About

Tobias Feldmann’s research centers on computer vision, with a particular focus on 3D egomotion estimation and visual odometry—critical technologies for augmented reality (AR) and autonomous robotics. His most cited work, “Dealing with degeneracy in essential matrix estimation” (2008, 8 citations), tackles a fundamental challenge in single-camera motion estimation: handling degenerate configurations that can cause algorithm failure. By proposing robust methods for essential matrix computation, Feldmann contributed to more reliable pose tracking in real-world scenarios where traditional approaches often break down. Though his citation count is modest, his work addresses a persistent problem in visual odometry, influencing subsequent research in AR and robotic navigation. Feldmann’s contributions are particularly relevant for systems requiring accurate, real-time motion estimation from video input—a cornerstone of modern immersive and autonomous technologies. His research underscores the importance of algorithmic robustness in practical computer vision applications.