Q Gautier
Papers
2
Total Citations
50
H-Index
2
About
Q. Gautier is a leading researcher at the intersection of reconfigurable computing and real-time computer vision, with a primary focus on enabling dense Simultaneous Localization And Mapping (SLAM) on Field-Programmable Gate Arrays (FPGAs). His seminal 2019 work, "FPGA Architectures for Real-time Dense SLAM" (33 citations), directly addressed the critical computational bottleneck of dense 3D reconstruction—a task far more demanding than traditional sparse SLAM—by proposing novel FPGA architectures that achieve real-time performance. This contribution is pivotal for advancing autonomous robotics, augmented reality, and virtual reality applications where low-latency, power-efficient processing is essential. Earlier, in his 2014 case study (17 citations), Gautier rigorously evaluated the performance, area, and programmability trade-offs of using the Altera OpenCL SDK for real-time 3D reconstruction from low-cost depth sensors. This work demonstrated a viable path to embedding complex vision algorithms on embedded platforms without relying on power-hungry desktop GPUs, thereby expanding the potential for mobile and untethered systems. Through these contributions, Gautier has established himself as a key figure in bridging the gap between high-level algorithm development and efficient hardware implementation for next-generation robotic and mixed-reality systems.
Research Focus
Key Achievements
Top Papers
- 1FPGA Architectures for Real-time Dense SLAM33 citations · 2019
- 2