About

Xavier Clady is a leading researcher in neuromorphic vision and assistive robotics, whose work bridges the gap between biological perception and artificial systems. His primary research areas include event-based vision, human-robot interaction, and embedded motion capture. Clady’s most impactful contribution is his pioneering work on asynchronous visual event-based time-to-contact estimation (2014, 57 citations), which introduced a paradigm-shifting method for fast, reliable sensing using neuromorphic sensors—overcoming the limitations of traditional frame-based cameras by leveraging their high temporal dynamics and low data redundancy. He also developed an event-based line and segment detection algorithm (2018, 34 citations), enabling luminance-free feature extraction from biomimetic retinas, a critical step for real-time robotic perception. In the domain of assistive robotics, Clady contributed to human detection systems for domestic robots (2011) and embedded 3D motion capture for walking assistive robots (2011), demonstrating practical applications in proxemics and rehabilitation. His work on the MIRAS project further highlights his commitment to multimodal interaction for mobility assistance. With a strong focus on efficiency and biological inspiration, Clady’s research continues to shape the future of autonomous systems and human-robot collaboration.

Research Focus

Key Achievements

4
H-Index
6
Papers
110
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Asynchronous visual event-based time-to-contact
57 citations · 2014
📈 Most Prolific Year: 2011 (2 Papers)
🤝 Key Collaborators: 27
🏛 Institutions: Institut de la Vision, Centre National de la Recherche Scientifique, Sorbonne Université, Institut Systèmes Intelligents et de Robotique

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago