Motoko Oe
Papers
2
Total Citations
35
H-Index
2
About
Motoko Oe is a researcher whose work lies at the intersection of computer vision, augmented reality, and robotics, with a particular focus on precise camera localization. Her most influential contribution is the development of a robust method for estimating camera position and posture using a feature landmark database. This vision-based approach offers a compelling alternative to sensor-dependent systems like GPS and magnetic sensors, which can be unreliable in indoor or obstructed environments. By leveraging pre-mapped visual landmarks, Oe’s technique enables accurate, absolute camera pose estimation from a single input image, a critical capability for augmented reality overlays and autonomous robot navigation. Her foundational 2005 paper on this method has garnered 33 citations, reflecting its impact as a practical solution for real-world spatial computing challenges. Through this work, Oe has helped bridge the gap between theoretical computer vision and applied systems, providing a cornerstone for technologies that require machines to understand their precise location in the physical world.
Research Focus
Key Achievements
Top Papers
- 1Estimating Camera Position and Posture by Using Feature Landmark Database33 citations · 2005
- 2