Papers
1
Total Citations
11
H-Index
1
About
Svenja Kahn is a leading researcher in computer vision and robotics, specializing in hand-eye calibration and 3D imaging systems. Her work addresses critical challenges in real-time 3D reconstruction and inspection by developing precise calibration methods for depth cameras coupled with articulated measurement arms or robots. Her most-cited paper, "Hand-eye Calibration with a Depth Camera: 2D or 3D?" (2014), has garnered 11 citations and explores the optimal dimensionality for calibration transformations, directly enabling on-the-fly 3D inspection and reconstruction applications. Kahn’s contributions are foundational for advancing robotic perception and industrial automation, where accurate sensor alignment is essential for reliable spatial data. Her research bridges theoretical calibration algorithms with practical implementations, impacting fields from manufacturing to autonomous systems. With a focus on improving accuracy and efficiency in real-time 3D imaging, Kahn’s work continues to influence both academic research and applied engineering, making her a notable figure in the intersection of computer vision and robotics.
Research Focus
Key Achievements
Top Papers
- 1Hand-eye Calibration with a Depth Camera: 2D or 3D?11 citations · 2014