Jean-Louis Boizard

About

Jean-Louis Boizard is a leading researcher in real-time embedded vision systems, with a focus on FPGA-based architectures for robotic and medical applications. His major contributions lie in the development of high-speed image processing algorithms, including color and texture classification, inverse perspective mapping for obstacle detection, and passive stereovision for 3D reconstruction. Notably, his work on a real-time stereovision system for laparoscopic surgery (2006, 8 citations) provides quantitative 3D information to enhance precision in surgical manipulations—a significant advancement over existing qualitative systems. Boizard’s designs, such as the FPGA-based obstacle detection system using a belt of micro-cameras (2009, 4 citations), enable mobile robots to navigate cluttered, dynamic environments with real-time performance. His research has garnered over 29 citations across key publications, demonstrating its impact on embedded vision and robotics. By bridging hardware acceleration and complex vision tasks, Boizard has advanced practical applications in autonomous navigation and medical imaging, making his work essential for students and engineers developing efficient, real-time visual systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Real-time classification based on color and texture attributes on an FPGA-based architecture

   8 citations · 2010
2. 2
   A 3D real-time vision system based on passive stereovision algorithms: Application to laparoscopic surgical manipulations

   8 citations · 2006
3. 3
   Real-time architecture on FPGA for obstacle detection using inverse perspective mapping

   7 citations · 2011
4. 4
   Integrated subsystem for Obstacle detection from a belt of micro-cameras

   4 citations · 2009
5. 5
   REAL-TIME STEREOVISION BY AN INTEGRATED SENSOR

   2 citations · 2007

Key Collaborators

Contact & Links