Anders Heyden
Papers
13
Total Citations
118
H-Index
7
About
Anders Heyden has made foundational contributions to computer vision and robot vision, particularly in camera calibration and ego-motion estimation. His research focuses on simplifying and extending calibration techniques for robotic systems, enabling more accurate and efficient visual perception. Heyden’s most cited work, “Simplified intrinsic camera calibration and hand-eye calibration for robot vision” (2004, 23 citations), introduces methods using minimal motions and planar objects, significantly reducing complexity in robot vision setups. He further advanced this field with extensions for translational motion (2006, 15 citations) and self-calibration from image derivatives for active vision systems (2004, 6 citations). His 1997 “A Computer Vision Toolbox” (14 citations) provided a practical resource for researchers and students. Heyden also contributed to ego-motion recovery for planar motion (2014, 7 citations) and visual odometry with automatic tilt calibration (2017, 5 citations). As an editor of the 7th European Conference on Computer Vision proceedings (2002, 12 citations) and the “Computer Analysis of Images and Patterns” series (2017, 10 citations), he has shaped the field’s discourse. With over 100 citations across his top works, Heyden’s impact lies in making calibration accessible and robust, directly benefiting autonomous robotics and 3D reconstruction.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3A Computer Vision Toolbox14 citations · 1997
- 4Proceedings of the 7th European Conference on Computer Vision-Part III12 citations · 2002
- 5Computer Analysis of Images and Patterns10 citations · 2017
- 6Computer Analysis of Images and Patterns10 citations · 2017
- 7
- 8Self-calibration from image derivatives for active vision systems6 citations · 2004
- 9Hand-Eye Calibration from Image Derivatives6 citations · 2000
- 10