Papers
17
Total Citations
164
H-Index
6
About
David Fofi is a distinguished researcher whose work spans computer vision, robotics, and polarimetric imaging, with particular expertise in 3D reconstruction, visual sensing, and autonomous robot navigation. His early contributions to uncalibrated vision using structured light — explored in his 2002 and 2003 papers (each garnering 33 citations) — offered elegant solutions to a longstanding challenge in mobile robotics: enabling reliable 3D environmental mapping without the constraints of traditional camera calibration, thereby advancing robotic autonomy significantly. Fofi has also made notable strides in polarization-based imaging, developing a widely recognized calibration framework for division-of-amplitude polarimeters (2016, 33 citations) and exploring bio-inspired polarization techniques drawn from animal vision systems. His survey on vision-based SLAM (2009, 17 citations) reflects his broader commitment to synthesizing foundational knowledge for the robotics community, while his 2024 work on robust tracking control for wheeled mobile robots demonstrates his continued relevance at the frontier of autonomous systems research. Beyond technical innovation, Fofi has actively shaped European computer vision education through high-profile Erasmus Mundus programs including VIBOT, CIMET, and EMARO, cementing his legacy as both a scientific contributor and an influential educator.
Research Focus
Key Achievements
Top Papers
- 1
- 2Uncalibrated reconstruction: an adaptation to structured light vision33 citations · 2003
- 3Uncalibrated vision based on structured light22 citations · 2002
- 4
- 5Current state of the art of vision based SLAM17 citations · 2009
- 6Static and Dynamic Objects Analysis as a 3D Vector Field7 citations · 2017
- 7View Planning Approach for Automatic 3D Digitization of Unknown Objects6 citations · 2012
- 8
- 9
- 10A 3D Scanner for Transparent Glass3 citations · 2009