Jean‐Philippe Domenger

About

Jean-Philippe Domenger is a leading researcher in computer vision and embedded systems, with a focus on real-time 3D reconstruction and wearable robotics. His work bridges the gap between advanced perception algorithms and practical, low-power hardware implementations. Domenger’s major contributions include pioneering FPGA-based implementations of the Scale-Invariant Feature Transform (SIFT) for wearable computing, enabling lightweight, portable systems for robotic arm and prosthetic control through real-time visual analysis. He has also advanced stereo-based Simultaneous Localization and Mapping (SLAM) by developing adaptive methods and synthetic stereo dataset generation for dense 3D reconstruction, directly supporting autonomous navigation and mapping. While his most-cited paper (5 citations) marks early steps in wearable vision, his broader impact lies in pushing the boundaries of real-time, embedded computer vision for robotics and autonomous systems. Domenger’s work is particularly notable for its emphasis on practical, deployable solutions, making him a key figure in the integration of SLAM and deep learning for autonomous vehicles and assistive technologies.

Research Focus

Key Achievements

Top Papers

1. 1
   FPGA-based SIFT implementation for wearable computing

   5 citations · 2019
2. 2
   Adaptive SLAM with Synthetic Stereo Dataset Generation for Real-time Dense 3D Reconstruction

   2 citations · 2019

Key Collaborators

Contact & Links