Papers
5
Total Citations
26
H-Index
3
About
Yohan Fougerolle is a researcher whose work sits at the intersection of robotics, computer vision, and three-dimensional scene understanding. His research spans autonomous digitization systems, dynamic scene analysis, and multimodal robotic sensing — areas with significant practical implications for both industrial automation and security applications. One of Fougerolle's earliest notable contributions was his involvement in the SAFER vehicle inspection platform (2004), a multimodal robotic sensing system developed to address national security concerns, particularly the protection of military bases, federal buildings, and critical infrastructure — work that has garnered 9 citations. He has also made meaningful strides in autonomous 3D digitization, developing fully automatic systems capable of scanning unknown objects without prior shape knowledge, combining fringe projection scanners with robotic arms and turntables in elegant two-step methodologies. More recently, Fougerolle has advanced dynamic scene analysis, proposing frameworks that represent static and moving scene elements as 3D vector fields and developing techniques for incomplete 3D motion trajectory segmentation with 2D-to-3D label transfer. These contributions support robust robot navigation and scene modelling in complex, real-world environments. While still building his citation profile, his research demonstrates a consistent commitment to bridging theoretical computer vision with applied robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Static and Dynamic Objects Analysis as a 3D Vector Field7 citations · 2017
- 3View Planning Approach for Automatic 3D Digitization of Unknown Objects6 citations · 2012
- 4Fully automatic 3D digitization of unknown objects2 citations · 2010
- 5