Jean Yves Ertaud

Papers

1

Total Citations

3

H-Index

1

About

Jean Yves Ertaud is a researcher specializing in computer vision, robotics, and intelligent surveillance systems, with particular expertise in multimodal sensor fusion and biometric authentication. His work focuses on developing advanced vision architectures that bridge the gap between wide-area monitoring and high-resolution identification, a challenge central to modern autonomous and security systems. His most notable contribution involves the design of an innovative hybrid vision system that combines catadioptric omnidirectional sensors with Pan-Tilt-Zoom (PTZ) cameras for face detection and recognition in mobile robotic contexts. This approach addresses a longstanding trade-off in robotic perception — the tension between broad environmental coverage and the fine-grained resolution needed for reliable biometric identification. By fusing heterogeneous database sources alongside complementary sensor modalities, Ertaud's system enables robust real-world authentication across dynamic environments. While his citation count remains modest, reflecting either a highly specialized niche or an emerging body of work, the technical sophistication of his research positions him as a contributor to the growing intersection of autonomous robotics, computer vision, and security technology — fields increasingly critical in smart infrastructure, human-robot interaction, and access control applications.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Face Detection and Recognition based on Fusion of Omnidirectional and PTZ Vision Sensors and Heteregenous Database
3 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 2

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago