Ehsan Fazl-Ersi
Papers
5
Total Citations
61
H-Index
3
About
Dr. Ehsan Fazl-Ersi is a leading researcher in computer vision and robotics, with a primary focus on scene understanding, human-robot interaction, and autonomous navigation. His most influential work introduces the **Histogram of Oriented Uniform Patterns**, a novel context-based method that enables mobile robots to robustly recognize and categorize topological places, achieving 45 citations and laying foundational groundwork for place recognition in unknown environments. Dr. Fazl-Ersi has also advanced safe human-robot collaboration by developing vision-based distance estimation systems using Kinect sensors for SCARA robots, enhancing workplace safety. His research extends to embedded multispectral pedestrian detection with the **MDSSD-MobV2** architecture, optimized for real-time performance on resource-constrained devices. Additionally, he has contributed to autonomous surveillance through the **Trackerbot** system, which integrates stereo-vision and artificial neural networks for fully automatic, calibration-free target tracking. With a career spanning over a decade, Dr. Fazl-Ersi’s work bridges theoretical innovation and practical deployment, making significant impacts in robotics, surveillance, and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Safe collaboration of humans and SCARA robots6 citations · 2016
- 3Hierarchical Classifiers for Robust Topological Robot Localization4 citations · 2012
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- 5